| 3D Face Synthesis Driven by Personality Impression |
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❌ |
✅ |
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❌ |
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3 |
| 3D Object Detection Using Scale Invariant and Feature Reweighting Networks |
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3 |
| 3D Volumetric Modeling with Introspective Neural Networks |
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3 |
| A Bandit Approach to Maximum Inner Product Search |
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3 |
| A Better Algorithm for Societal Tradeoffs |
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2 |
| A Bottom-Up Clustering Approach to Unsupervised Person Re-Identification |
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5 |
| A Bridge between Liquid and Social Welfare in Combinatorial Auctions with Submodular Bidders |
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1 |
| A Comparative Analysis of Expected and Distributional Reinforcement Learning |
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❌ |
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1 |
| A Deep Cascade Model for Multi-Document Reading Comprehension |
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✅ |
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✅ |
✅ |
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5 |
| A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data |
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✅ |
✅ |
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3 |
| A Deep Reinforcement Learning Based Multi-Step Coarse to Fine Question Answering (MSCQA) System |
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✅ |
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❌ |
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3 |
| A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems |
✅ |
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✅ |
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3 |
| A Deep Sequential Model for Discourse Parsing on Multi-Party Dialogues |
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✅ |
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3 |
| A Distillation Approach to Data Efficient Individual Treatment Effect Estimation |
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✅ |
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3 |
| A Domain Generalization Perspective on Listwise Context Modeling |
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✅ |
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3 |
| A Dual Attention Network with Semantic Embedding for Few-Shot Learning |
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✅ |
✅ |
✅ |
❌ |
❌ |
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3 |
| A Framework for Approval-Based Budgeting Methods |
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❌ |
❌ |
✅ |
✅ |
2 |
| A Framework to Coordinate Segmentation and Recognition |
✅ |
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✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| A Generalized Idiom Usage Recognition Model Based on Semantic Compatibility |
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✅ |
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❌ |
❌ |
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2 |
| A Generalized Language Model in Tensor Space |
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✅ |
✅ |
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3 |
| A Generative Model for Dynamic Networks with Applications |
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❌ |
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2 |
| A Generic Approach to Accelerating Belief Propagation Based Incomplete Algorithms for DCOPs via a Branch-and-Bound Technique |
✅ |
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❌ |
❌ |
❌ |
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2 |
| A Grammar-Based Structural CNN Decoder for Code Generation |
❌ |
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✅ |
❌ |
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4 |
| A Hierarchical Framework for Relation Extraction with Reinforcement Learning |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| A Hierarchical Multi-Task Approach for Learning Embeddings from Semantic Tasks |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| A Human-Like Semantic Cognition Network for Aspect-Level Sentiment Classification |
❌ |
❌ |
✅ |
❌ |
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❌ |
✅ |
2 |
| A Layer Decomposition-Recomposition Framework for Neuron Pruning towards Accurate Lightweight Networks |
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❌ |
✅ |
✅ |
✅ |
✅ |
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5 |
| A Layer-Based Sequential Framework for Scene Generation with GANs |
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✅ |
✅ |
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❌ |
❌ |
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4 |
| A Memetic Approach for Sequential Security Games on a Plane with Moving Targets |
✅ |
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❌ |
❌ |
✅ |
✅ |
✅ |
4 |
| A Model-Free Affective Reinforcement Learning Approach to Personalization of an Autonomous Social Robot Companion for Early Literacy Education |
❌ |
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❌ |
❌ |
❌ |
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1 |
| A Multi-Agent Communication Framework for Question-Worthy Phrase Extraction and Question Generation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
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3 |
| A Natural Language Corpus of Common Grounding under Continuous and Partially-Observable Context |
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✅ |
✅ |
✅ |
❌ |
❌ |
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4 |
| A Neural Multi-Task Learning Framework to Jointly Model Medical Named Entity Recognition and Normalization |
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✅ |
✅ |
✅ |
❌ |
❌ |
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4 |
| A Neural Network Approach to Verb Phrase Ellipsis Resolution |
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✅ |
✅ |
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❌ |
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4 |
| A New Ensemble Learning Framework for 3D Biomedical Image Segmentation |
✅ |
✅ |
✅ |
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❌ |
✅ |
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6 |
| A Nonconvex Projection Method for Robust PCA |
✅ |
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✅ |
3 |
| A Non–Convex Optimization Approach to Correlation Clustering |
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❌ |
✅ |
3 |
| A Novel Framework for Robustness Analysis of Visual QA Models |
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✅ |
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3 |
| A PAC Framework for Aggregating Agents’ Judgments |
✅ |
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1 |
| A PSPACE Subclass of Dependency Quantified Boolean Formulas and Its Effective Solving |
✅ |
✅ |
✅ |
❌ |
✅ |
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✅ |
5 |
| A Pattern-Based Approach to Recognizing Time Expressions |
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✅ |
✅ |
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❌ |
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5 |
| A Powerful Global Test Statistic for Functional Statistical Inference |
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3 |
| A Probabilistic Derivation of LASSO and L12-Norm Feature Selections |
✅ |
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❌ |
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4 |
| A Radical-Aware Attention-Based Model for Chinese Text Classification |
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✅ |
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3 |
| A Recursive Algorithm for Projected Model Counting |
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6 |
| A Robust and Efficient Algorithm for the PnL Problem Using Algebraic Distance to Approximate the Reprojection Distance |
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4 |
| A SAT+CAS Approach to Finding Good Matrices: New Examples and Counterexamples |
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3 |
| A Sequential Set Generation Method for Predicting Set-Valued Outputs |
✅ |
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✅ |
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3 |
| A Sharper Generalization Bound for Divide-and-Conquer Ridge Regression |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| A Study of Educational Data Mining: Evidence from a Thai University |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
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1 |
| A Task in a Suit and a Tie: Paraphrase Generation with Semantic Augmentation |
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✅ |
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4 |
| A Theoretically Guaranteed Deep Optimization Framework for Robust Compressive Sensing MRI |
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4 |
| A Topic-Aware Reinforced Model for Weakly Supervised Stance Detection |
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4 |
| A Two-Individual Based Evolutionary Algorithm for the Flexible Job Shop Scheduling Problem |
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✅ |
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❌ |
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5 |
| A Two-Stream Mutual Attention Network for Semi-Supervised Biomedical Segmentation with Noisy Labels |
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3 |
| A Unified Approach to Online Matching with Conflict-Aware Constraints |
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4 |
| A Unified Framework for Planning in Adversarial and Cooperative Environments |
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4 |
| A Unified Model for Opinion Target Extraction and Target Sentiment Prediction |
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4 |
| A2-Net: Molecular Structure Estimation from Cryo-EM Density Volumes |
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2 |
| ABox Abduction via Forgetting in ALC |
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4 |
| ACE: An Actor Ensemble Algorithm for Continuous Control with Tree Search |
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3 |
| ACM: Adaptive Cross-Modal Graph Convolutional Neural Networks for RGB-D Scene Recognition |
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✅ |
✅ |
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❌ |
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5 |
| AFS: An Attention-Based Mechanism for Supervised Feature Selection |
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✅ |
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4 |
| AI-Sketcher : A Deep Generative Model for Producing High-Quality Sketches |
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❌ |
✅ |
❌ |
✅ |
❌ |
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3 |
| ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning |
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✅ |
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❌ |
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3 |
| ATP: Directed Graph Embedding with Asymmetric Transitivity Preservation |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
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2 |
| Abduction-Based Explanations for Machine Learning Models |
✅ |
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✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Abstracting Causal Models |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
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0 |
| Abstractive Text Summarization by Incorporating Reader Comments |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Accurate and Interpretable Factorization Machines |
✅ |
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✅ |
✅ |
❌ |
❌ |
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4 |
| Acting and Planning Using Operational Models |
✅ |
✅ |
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❌ |
✅ |
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4 |
| Action Knowledge Transfer for Action Prediction with Partial Videos |
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❌ |
✅ |
✅ |
❌ |
❌ |
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3 |
| Active Generative Adversarial Network for Image Classification |
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✅ |
✅ |
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❌ |
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4 |
| Active Learning of Multi-Class Classification Models from Ordered Class Sets |
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✅ |
❌ |
❌ |
❌ |
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1 |
| Active Mini-Batch Sampling Using Repulsive Point Processes |
✅ |
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✅ |
✅ |
❌ |
✅ |
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5 |
| Active Preference Learning Based on Generalized Gini Functions: Application to the Multiagent Knapsack Problem |
✅ |
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❌ |
❌ |
✅ |
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3 |
| Active Sampling for Open-Set Classification without Initial Annotation |
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✅ |
❌ |
❌ |
❌ |
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3 |
| ActivityNet-QA: A Dataset for Understanding Complex Web Videos via Question Answering |
❌ |
❌ |
✅ |
✅ |
❌ |
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3 |
| Adapting Translation Models for Transcript Disfluency Detection |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Adaptive Proximal Average Based Variance Reducing Stochastic Methods for Optimization with Composite Regularization |
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❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Adaptive Region Embedding for Text Classification |
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❌ |
✅ |
❌ |
❌ |
❌ |
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2 |
| Adaptive Sparse Confidence-Weighted Learning for Online Feature Selection |
✅ |
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✅ |
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❌ |
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3 |
| Adding Constraints to Bayesian Inverse Problems |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
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1 |
| Addressing the Under-Translation Problem from the Entropy Perspective |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Adversarial Actor-Critic Method for Task and Motion Planning Problems Using Planning Experience |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
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2 |
| Adversarial Binary Collaborative Filtering for Implicit Feedback |
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✅ |
✅ |
❌ |
❌ |
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4 |
| Adversarial Dropout for Recurrent Neural Networks |
❌ |
✅ |
✅ |
✅ |
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❌ |
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4 |
| Adversarial Label Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
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4 |
| Adversarial Learning for Weakly-Supervised Social Network Alignment |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
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3 |
| Adversarial Learning of Semantic Relevance in Text to Image Synthesis |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
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3 |
| Adversarial Training for Community Question Answer Selection Based on Multi-Scale Matching |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Adversarial Unsupervised Representation Learning for Activity Time-Series |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| AffinityNet: Semi-Supervised Few-Shot Learning for Disease Type Prediction |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
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3 |
| Algorithms for Average Regret Minimization |
❌ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
4 |
| Algorithms for Estimating Trends in Global Temperature Volatility |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
6 |
| Aligning Domain-Specific Distribution and Classifier for Cross-Domain Classification from Multiple Sources |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Allocating Interventions Based on Predicted Outcomes: A Case Study on Homelessness Services |
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❌ |
❌ |
❌ |
❌ |
❌ |
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1 |
| Allocating Planning Effort When Actions Expire |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Almost Unsupervised Learning for Dense Crowd Counting |
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❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Amalgamating Knowledge towards Comprehensive Classification |
✅ |
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✅ |
❌ |
✅ |
❌ |
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3 |
| An Abstraction-Based Method for Verifying Strategic Properties in Multi-Agent Systems with Imperfect Information |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| An Affect-Rich Neural Conversational Model with Biased Attention and Weighted Cross-Entropy Loss |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| An Efficient Approach to Informative Feature Extraction from Multimodal Data |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| An Efficient Compressive Convolutional Network for Unified Object Detection and Image Compression |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| An Equivalence between Wagering and Fair-Division Mechanisms |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| An Exponential Tail Bound for the Deleted Estimate |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| An Improved Generic Bet-and-Run Strategy with Performance Prediction for Stochastic Local Search |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| An Improved Quasi-Polynomial Algorithm for Approximate Well-Supported Nash Equilibria |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| An Innovative Genetic Algorithm for the Quantum Circuit Compilation Problem |
✅ |
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✅ |
❌ |
✅ |
❌ |
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4 |
| An Integral Tag Recommendation Model for Textual Content |
❌ |
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✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| An Open-World Extension to Knowledge Graph Completion Models |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Analysis of Joint Multilingual Sentence Representations and Semantic K-Nearest Neighbor Graphs |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
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3 |
| Analyzing Compositionality-Sensitivity of NLI Models |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
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4 |
| Anchors Bring Ease: An Embarrassingly Simple Approach to Partial Multi-View Clustering |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
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3 |
| Angular Triplet-Center Loss for Multi-View 3D Shape Retrieval |
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❌ |
✅ |
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✅ |
❌ |
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4 |
| Answer Identification from Product Reviews for User Questions by Multi-Task Attentive Networks |
❌ |
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✅ |
✅ |
❌ |
❌ |
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4 |
| Antonym-Synonym Classification Based on New Sub-Space Embeddings |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
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4 |
| Anytime Recursive Best-First Search for Bounding Marginal MAP |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Approximate Inference of Outcomes in Probabilistic Elections |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Approximate Kernel Selection with Strong Approximate Consistency |
✅ |
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✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Approximate Stream Reasoning with Metric Temporal Logic under Uncertainty |
✅ |
✅ |
❌ |
❌ |
✅ |
❌ |
✅ |
4 |
| Approximation and Hardness of Shift-Bribery |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Argumentation for Explainable Scheduling |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Asynchronous Delay-Aware Accelerated Proximal Coordinate Descent for Nonconvex Nonsmooth Problems |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Asynchronous Proximal Stochastic Gradient Algorithm for Composition Optimization Problems |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Attacking Data Transforming Learners at Training Time |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Attention-Aware Sampling via Deep Reinforcement Learning for Action Recognition |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Attention-Based Multi-Context Guiding for Few-Shot Semantic Segmentation |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Attentive Temporal Pyramid Network for Dynamic Scene Classification |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Attentive Tensor Product Learning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Augmenting Markov Decision Processes with Advising |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| AutoSense Model for Word Sense Induction |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Automated Rule Base Completion as Bayesian Concept Induction |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Automated Verification of Social Laws for Continuous Time Multi-Robot Systems |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Automatic Bayesian Density Analysis |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Automatic Code Review by Learning the Revision of Source Code |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Automatic Construction of Parallel Portfolios via Explicit Instance Grouping |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Automatic Detection and Compression for Passive Acoustic Monitoring of the African Forest Elephant |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Axiomatic Characterization of Data-Driven Influence Measures for Classification |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| BIRD: Engineering an Efficient CNF-XOR SAT Solver and Its Applications to Approximate Model Counting |
✅ |
✅ |
❌ |
❌ |
✅ |
❌ |
✅ |
4 |
| BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Backbone Cannot Be Trained at Once: Rolling Back to Pre-Trained Network for Person Re-Identification |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Balanced Linear Contextual Bandits |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Balanced Sparsity for Efficient DNN Inference on GPU |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Balancing Relevance and Diversity in Online Bipartite Matching via Submodularity |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Bayesian Deep Collaborative Matrix Factorization |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Bayesian Execution Skill Estimation |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Bayesian Fairness |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Bayesian Functional Optimisation with Shape Prior |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Bayesian Graph Convolutional Neural Networks for Semi-Supervised Classification |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Bayesian Posterior Approximation via Greedy Particle Optimization |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Be Inaccurate but Don’t Be Indecisive: How Error Distribution Can Affect User Experience |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Belief Change and Non-Monotonic Reasoning Sans Compactness |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Better Fine-Tuning via Instance Weighting for Text Classification |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Beyond Speech: Generalizing D-Vectors for Biometric Verification |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Bi-Kronecker Functional Decision Diagrams: A Novel Canonical Representation of Boolean Functions |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
3 |
| BiHMP-GAN: Bidirectional 3D Human Motion Prediction GAN |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Bias Reduction via End-to-End Shift Learning: Application to Citizen Science |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Bidirectional Inference Networks:A Class of Deep Bayesian Networks for Health Profiling |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Bidirectional Transition-Based Dependency Parsing |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Biologically Motivated Algorithms for Propagating Local Target Representations |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Biomedical Image Segmentation via Representative Annotation |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Blameworthiness in Multi-Agent Settings |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Blameworthiness in Strategic Games |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Block Belief Propagation for Parameter Learning in Markov Random Fields |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| Bootstrap Estimated Uncertainty of the Environment Model for Model-Based Reinforcement Learning |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Bounded Suboptimal Search with Learned Heuristics for Multi-Agent Systems |
❌ |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
2 |
| Bounding Uncertainty for Active Batch Selection |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Bringing Order to Chaos – A Compact Representation of Partial Order in SAT-Based HTN Planning |
❌ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
3 |
| Building Causal Graphs from Medical Literature and Electronic Medical Records |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| Bézier Simplex Fitting: Describing Pareto Fronts of´ Simplicial Problems with Small Samples in Multi-Objective Optimization |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
6 |
| CAFE: Adaptive VDI Workload Prediction with Multi-Grained Features |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| CAMO: A Collaborative Ranking Method for Content Based Recommendation |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| CAPNet: Continuous Approximation Projection for 3D Point Cloud Reconstruction Using 2D Supervision |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| CGMH: Constrained Sentence Generation by Metropolis-Hastings Sampling |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| CISI-net: Explicit Latent Content Inference and Imitated Style Rendering for Image Inpainting |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| COALA: A Neural Coverage-Based Approach for Long Answer Selection with Small Data |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Calibrated Stochastic Gradient Descent for Convolutional Neural Networks |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Capacity Control of ReLU Neural Networks by Basis-Path Norm |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Cash-Out User Detection Based on Attributed Heterogeneous Information Network with a Hierarchical Attention Mechanism |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Certifying the True Error: Machine Learning in Coq with Verified Generalization Guarantees |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Challenges in the Automatic Analysis of Students’ Diagnostic Reasoning |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Character n-Gram Embeddings to Improve RNN Language Models |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Character-Level Language Modeling with Deeper Self-Attention |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Chinese NER with Height-Limited Constituent Parsing |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| CircConv: A Structured Convolution with Low Complexity |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Clairvoyant Restarts in Branch-and-Bound Search Using Online Tree-Size Estimation |
❌ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
4 |
| Classification with Costly Features Using Deep Reinforcement Learning |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Clipped Matrix Completion: A Remedy for Ceiling Effects |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| ClusterGAN: Latent Space Clustering in Generative Adversarial Networks |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Cognitive Deficit of Deep Learning in Numerosity |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Cogra: Concept-Drift-Aware Stochastic Gradient Descent for Time-Series Forecasting |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| ColNet: Embedding the Semantics of Web Tables for Column Type Prediction |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Collaboration Based Multi-Label Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Collaborative, Dynamic and Diversified User Profiling |
✅ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Combined Reinforcement Learning via Abstract Representations |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Combining Axiom Injection and Knowledge Base Completion for Efficient Natural Language Inference |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Combining Deep Learning and Qualitative Spatial Reasoning to Learn Complex Structures from Sparse Examples with Noise |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Combining Fact Extraction and Verification with Neural Semantic Matching Networks |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Combo-Action: Training Agent For FPS Game with Auxiliary Tasks |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Communication-Efficient Stochastic Gradient MCMC for Neural Networks |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Communication-Optimal Distributed Dynamic Graph Clustering |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Community Detection in Social Networks Considering Topic Correlations |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Community Focusing: Yet Another Query-Dependent Community Detection |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Comparative Document Summarisation via Classification |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| CompareLDA: A Topic Model for Document Comparison |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Compiling Bayesian Network Classifiers into Decision Graphs |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Complex Moment-Based Supervised Eigenmap for Dimensionality Reduction |
✅ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
6 |
| Complex Unitary Recurrent Neural Networks Using Scaled Cayley Transform |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Complexity of Abstract Argumentation under a Claim-Centric View |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Complexity of Inconsistency-Tolerant Query Answering in Datalog+/– under Cardinality-Based Repairs |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Composable Modular Reinforcement Learning |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Composite Binary Decomposition Networks |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Computing the Yolk in Spatial Voting Games without Computing Median Lines |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Concurrency Debugging with MaxSMT |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
✅ |
5 |
| Confidence Weighted Multitask Learning |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Congestion Graphs for Automated Time Predictions |
❌ |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
3 |
| Connecting Language to Images: A Progressive Attention-Guided Network for Simultaneous Image Captioning and Language Grounding |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Connecting the Digital and Physical World: Improving the Robustness of Adversarial Attacks |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Consensual Affine Transformations for Partial Valuation Aggregation |
❌ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
3 |
| Consensus Adversarial Domain Adaptation |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
2 |
| Consensus in Opinion Formation Processes in Fully Evolving Environments |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Constraint-Based Sequential Pattern Mining with Decision Diagrams |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Context-Aware Self-Attention Networks |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Contextualized Non-Local Neural Networks for Sequence Learning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Convergence of Learning Dynamics in Information Retrieval Games |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Convex Formulations for Fair Principal Component Analysis |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Convolutional Spatial Attention Model for Reading Comprehension with Multiple-Choice Questions |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Cooperation Enforcement and Collusion Resistance in Repeated Public Goods Games |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Cooperative Multimodal Approach to Depression Detection in Twitter |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Coreset Stochastic Variance-Reduced Gradient with Application to Optimal Margin Distribution Machine |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Cost-Sensitive Learning to Rank |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Counterfactual Randomization: Rescuing Experimental Studies from Obscured Confounding |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
3 |
| Counting Complexity for Reasoning in Abstract Argumentation |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Counting and Sampling Markov Equivalent Directed Acyclic Graphs |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
3 |
| Counting and Sampling from Markov Equivalent DAGs Using Clique Trees |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Coupled CycleGAN: Unsupervised Hashing Network for Cross-Modal Retrieval |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Cousin Network Guided Sketch Recognition via Latent Attribute Warehouse |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Covariate Shift Adaptation on Learning from Positive and Unlabeled Data |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Coverage Centrality Maximization in Undirected Networks |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Crash to Not Crash: Learn to Identify Dangerous Vehicles Using a Simulator |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Crawling the Community Structure of Multiplex Networks |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Cross-Domain Visual Representations via Unsupervised Graph Alignment |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Cross-Relation Cross-Bag Attention for Distantly-Supervised Relation Extraction |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Cross-View Local Structure Preserved Diversity and Consensus Learning for Multi-View Unsupervised Feature Selection |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Cubic LSTMs for Video Prediction |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Cycle-SUM: Cycle-Consistent Adversarial LSTM Networks for Unsupervised Video Summarization |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| CycleEmotionGAN: Emotional Semantic Consistency Preserved CycleGAN for Adapting Image Emotions |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| DAN: Deep Attention Neural Network for News Recommendation |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| DDFlow: Learning Optical Flow with Unlabeled Data Distillation |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| DRr-Net: Dynamic Re-Read Network for Sentence Semantic Matching |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| DTMT: A Novel Deep Transition Architecture for Neural Machine Translation |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Data Augmentation Based on Adversarial Autoencoder Handling Imbalance for Learning to Rank |
❌ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
5 |
| Data Augmentation for Spoken Language Understanding via Joint Variational Generation |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Data Fine-Tuning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Data-Adaptive Metric Learning with Scale Alignment |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Data-Distortion Guided Self-Distillation for Deep Neural Networks |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Data-to-Text Generation with Content Selection and Planning |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| DeRPN: Taking a Further Step toward More General Object Detection |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Deception in Finitely Repeated Security Games |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Declarative Question Answering over Knowledge Bases Containing Natural Language Text with Answer Set Programming |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
4 |
| Deep Bayesian Optimization on Attributed Graphs |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Deep Bayesian Trust: A Dominant and Fair Incentive Mechanism for Crowd |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Deep Cascade Multi-Task Learning for Slot Filling in Online Shopping Assistant |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Deep Convolutional Sum-Product Networks |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Deep Embedding Features for Salient Object Detection |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Deep Hierarchical Graph Convolution for Election Prediction from Geospatial Census Data |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| Deep Interest Evolution Network for Click-Through Rate Prediction |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Deep Latent Generative Models for Energy Disaggregation |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Deep Learning for Cost-Optimal Planning: Task-Dependent Planner Selection |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Deep Metric Learning by Online Soft Mining and Class-Aware Attention |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Deep Neural Network Quantization via Layer-Wise Optimization Using Limited Training Data |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Deep Neural Networks Constrained by Decision Rules |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Deep Reactive Policies for Planning in Stochastic Nonlinear Domains |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Deep Recurrent Survival Analysis |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Deep Reinforcement Learning for Green Security Games with Real-Time Information |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Deep Reinforcement Learning for Syntactic Error Repair in Student Programs |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Deep Robust Unsupervised Multi-Modal Network |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Deep Short Text Classification with Knowledge Powered Attention |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Deep Single-View 3D Object Reconstruction with Visual Hull Embedding |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Deep Transformation Method for Discriminant Analysis of Multi-Channel Resting State fMRI |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Deep Video Frame Interpolation Using Cyclic Frame Generation |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| DeepCCFV: Camera Constraint-Free Multi-View Convolutional Neural Network for 3D Object Retrieval |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| DeepChannel: Salience Estimation by Contrastive Learning for Extractive Document Summarization |
✅ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
6 |
| DeepDPM: Dynamic Population Mapping via Deep Neural Network |
❌ |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
3 |
| DeepETA: A Spatial-Temporal Sequential Neural Network Model for Estimating Time of Arrival in Package Delivery System |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| DeepFuzz: Automatic Generation of Syntax Valid C Programs for Fuzz Testing |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| DeepSTN+: Context-Aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| DeepTileBars: Visualizing Term Distribution for Neural Information Retrieval |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Deeply Fusing Reviews and Contents for Cold Start Users in Cross-Domain Recommendation Systems |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Defending Elections against Malicious Spread of Misinformation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Deictic Image Mapping: An Abstraction for Learning Pose Invariant Manipulation Policies |
❌ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
2 |
| Deliberate Attention Networks for Image Captioning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Densely Supervised Grasp Detector (DSGD) |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Dependency Grammar Induction with a Neural Variational Transition-Based Parser |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Dependency or Span, End-to-End Uniform Semantic Role Labeling |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Depth Prediction without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Depthwise Convolution Is All You Need for Learning Multiple Visual Domains |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Deriving Subgoals Autonomously to Accelerate Learning in Sparse Reward Domains |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
✅ |
5 |
| Detect or Track: Towards Cost-Effective Video Object Detection/Tracking |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Detecting Incongruity between News Headline and Body Text via a Deep Hierarchical Encoder |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Determinantal Reinforcement Learning |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Devil in the Details: Towards Accurate Single and Multiple Human Parsing |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Dialogue Generation: From Imitation Learning to Inverse Reinforcement Learning |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| DialogueRNN: An Attentive RNN for Emotion Detection in Conversations |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| Dictionary-Guided Editing Networks for Paraphrase Generation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Differential Networks for Visual Question Answering |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Differentially Private Empirical Risk Minimization with Smooth Non-Convex Loss Functions: A Non-Stationary View |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Differentiated Distribution Recovery for Neural Text Generation |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Difficulty-Aware Attention Network with Confidence Learning for Medical Image Segmentation |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Dimension-Free Error Bounds from Random Projections |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Direct Training for Spiking Neural Networks: Faster, Larger, Better |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Dirichlet Multinomial Mixture with Variational Manifold Regularization: Topic Modeling over Short Texts |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Discrete Social Recommendation |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Discriminative Feature Learning for Unsupervised Video Summarization |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Disentangled Variational Representation for Heterogeneous Face Recognition |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Disjoint Label Space Transfer Learning with Common Factorised Space |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Disjunctive Normal Form for Multi-Agent Modal Logics Based on Logical Separability |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Distant Supervision for Relation Extraction with Linear Attenuation Simulation and Non-IID Relevance Embedding |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Distantly Supervised Entity Relation Extraction with Adapted Manual Annotations |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Distributed Community Detection via Metastability of the 2-Choices Dynamics |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Distributed PageRank Computation: An Improved Theoretical Study |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Distributed Representation of Words in Cause and Effect Spaces |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Distribution Consistency Based Covariance Metric Networks for Few-Shot Learning |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Distribution-Based Semi-Supervised Learning for Activity Recognition |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Distributional Semantics Meets Multi-Label Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Distributionally Adversarial Attack |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Distributionally Robust Semi-Supervised Learning for People-Centric Sensing |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Diverse Exploration via Conjugate Policies for Policy Gradient Methods |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Diversity-Driven Extensible Hierarchical Reinforcement Learning |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| DoPAMINE: Double-Sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Document Informed Neural Autoregressive Topic Models with Distributional Prior |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
4 |
| Domain Agnostic Real-Valued Specificity Prediction |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Dual Semi-Supervised Learning for Facial Action Unit Recognition |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Dual-View Ranking with Hardness Assessment for Zero-Shot Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Dueling Bandits with Qualitative Feedback |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| DyS: A Framework for Mixture Models in Quantification |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Dynamic Capsule Attention for Visual Question Answering |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Dynamic Compositionality in Recursive Neural Networks with Structure-Aware Tag Representations |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Dynamic Contracting under Positive Commitment |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Dynamic Explainable Recommendation Based on Neural Attentive Models |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Dynamic Layer Aggregation for Neural Machine Translation with Routing-by-Agreement |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Dynamic Learning of Sequential Choice Bandit Problem under Marketing Fatigue |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Dynamic Spatial-Temporal Graph Convolutional Neural Networks for Traffic Forecasting |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| EA Reader: Enhance Attentive Reader for Cloze-Style Question Answering via Multi-Space Context Fusion |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| EA-CG: An Approximate Second-Order Method for Training Fully-Connected Neural Networks |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Efficient Concept Induction for Description Logics |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Efficient Counterfactual Learning from Bandit Feedback |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Efficient Data Point Pruning for One-Class SVM |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Efficient Gaussian Process Classification Using Pólya-Gamma Data Augmentation |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
5 |
| Efficient Identification of Approximate Best Configuration of Training in Large Datasets |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Efficient Image Retrieval via Decoupling Diffusion into Online and Offline Processing |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Efficient Online Learning for Mapping Kernels on Linguistic Structures |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Efficient Optimal Approximation of Discrete Random Variables for Estimation of Probabilities of Missing Deadlines |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Efficient Quantization for Neural Networks with Binary Weights and Low Bitwidth Activations |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Efficient Region Embedding with Multi-View Spatial Networks: A Perspective of Locality-Constrained Spatial Autocorrelations |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Efficient Temporal Planning Using Metastates |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Efficient and Effective Incomplete Multi-View Clustering |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Efficient and Scalable Multi-Task Regression on Massive Number of Tasks |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Efficiently Combining Human Demonstrations and Interventions for Safe Training of Autonomous Systems in Real-Time |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Efficiently Reasoning with Interval Constraints in Forward Search Planning |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
❌ |
2 |
| Election with Bribed Voter Uncertainty: Hardness and Approximation Algorithm |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Eliminating Latent Discrimination: Train Then Mask |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Embedding Uncertain Knowledge Graphs |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Embedding-Based Complex Feature Value Coupling Learning for Detecting Outliers in Non-IID Categorical Data |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| End-to-End Knowledge-Routed Relational Dialogue System for Automatic Diagnosis |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| End-to-End Structure-Aware Convolutional Networks for Knowledge Base Completion |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Energy Confused Adversarial Metric Learning for Zero-Shot Image Retrieval and Clustering |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Enhanced Random Forest Algorithms for Partially Monotone Ordinal Classification |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Enhancing Lazy Grounding with Lazy Normalization in Answer-Set Programming |
✅ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
4 |
| Enriching Non-Parametric Bidirectional Search Algorithms |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Enriching Word Embeddings with a Regressor Instead of Labeled Corpora |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| EnsNet: Ensconce Text in the Wild |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Entity Alignment between Knowledge Graphs Using Attribute Embeddings |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Estimating the Causal Effect from Partially Observed Time Series |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Estimating the Days to Success of Campaigns in Crowdfunding: A Deep Survival Perspective |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Evaluating Recommender System Stability with Influence-Guided Fuzzing |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Evolution of Collective Fairness in Hybrid Populations of Humans and Agents |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Evolutionarily Learning Multi-Aspect Interactions and Influences from Network Structure and Node Content |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Evolutionary Manytasking Optimization Based on Symbiosis in Biocoenosis |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Evolving Action Abstractions for Real-Time Planning in Extensive-Form Games |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
3 |
| Evolving Solutions to Community-Structured Satisfiability Formulas |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Exact and Approximate Weighted Model Integration with Probability Density Functions Using Knowledge Compilation |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Explainable Reasoning over Knowledge Graphs for Recommendation |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Explainable Recommendation through Attentive Multi-View Learning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Explicit Interaction Model towards Text Classification |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Exploiting Background Knowledge in Compact Answer Generation for Why-Questions |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Exploiting Class Learnability in Noisy Data |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| Exploiting Coarse-to-Fine Task Transfer for Aspect-Level Sentiment Classification |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Exploiting Local Feature Patterns for Unsupervised Domain Adaptation |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Exploiting Sentence Embedding for Medical Question Answering |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Exploiting Time-Series Image-to-Image Translation to Expand the Range of Wildlife Habitat Analysis |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| Exploiting the Contagious Effect for Employee Turnover Prediction |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Exploiting the Ground-Truth: An Adversarial Imitation Based Knowledge Distillation Approach for Event Detection |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Exploring Answer Stance Detection with Recurrent Conditional Attention |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Exploring Human-Like Reading Strategy for Abstractive Text Summarization |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Exploring Knowledge Graphs in an Interpretable Composite Approach for Text Entailment |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Extension Removal in Abstract Argumentation – An Axiomatic Approach |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| FANDA: A Novel Approach to Perform Follow-Up Query Analysis |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| FLEX: Faithful Linguistic Explanations for Neural Net Based Model Decisions |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| FRAME Revisited: An Interpretation View Based on Particle Evolution |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Fair Division with a Secretive Agent |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Fair Knapsack |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Fair and Efficient Memory Sharing: Confronting Free Riders |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Fairly Allocating Many Goods with Few Queries |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Fast Incremental SVDD Learning Algorithm with the Gaussian Kernel |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Fast Iterative Combinatorial Auctions via Bayesian Learning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Fast PMI-Based Word Embedding with Efficient Use of Unobserved Patterns |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
3 |
| Fast and Simple Mixture of Softmaxes with BPE and Hybrid-LightRNN for Language Generation |
❌ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
5 |
| Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Feature Sampling Based Unsupervised Semantic Clustering for Real Web Multi-View Content |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Few-Shot Image and Sentence Matching via Gated Visual-Semantic Embedding |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Find Me if You Can: Deep Software Clone Detection by Exploiting the Contest between the Plagiarist and the Detector |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Finding All Bayesian Network Structures within a Factor of Optimal |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Fine-Grained Search Space Classification for Hard Enumeration Variants of Subset Problems |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Forbidden Nodes Aware Community Search |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Forgetting in Modular Answer Set Programming |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Forming Probably Stable Communities with Limited Interactions |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Found in Translation: Learning Robust Joint Representations by Cyclic Translations between Modalities |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| Frame and Feature-Context Video Super-Resolution |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Free VQA Models from Knowledge Inertia by Pairwise Inconformity Learning |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| From Horn-SRIQ to Datalog: A Data-Independent Transformation That Preserves Assertion Entailment |
❌ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
4 |
| From Independent Prediction to Reordered Prediction: Integrating Relative Position and Global Label Information to Emotion Cause Identification |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| From Recommendation Systems to Facility Location Games |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| From Zero-Shot Learning to Cold-Start Recommendation |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| Fully Convolutional Network with Multi-Step Reinforcement Learning for Image Processing |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Fully Convolutional Video Captioning with Coarse-to-Fine and Inherited Attention |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Functional Connectivity Network Analysis with Discriminative Hub Detection for Brain Disease Identification |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Fuzzy-Classification Assisted Solution Preselection in Evolutionary Optimization |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| G2C: A Generator-to-Classifier Framework Integrating Multi-Stained Visual Cues for Pathological Glomerulus Classification |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination |
✅ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
6 |
| GIRNet: Interleaved Multi-Task Recurrent State Sequence Models |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| GRN: Gated Relation Network to Enhance Convolutional Neural Network for Named Entity Recognition |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Gated Residual Recurrent Graph Neural Networks for Traffic Prediction |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Gaussian Transformer: A Lightweight Approach for Natural Language Inference |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Gaussian-Induced Convolution for Graphs |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| General Robustness Evaluation of Incentive Mechanism against Bounded Rationality Using Continuum-Armed Bandits |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Generalized Batch Normalization: Towards Accelerating Deep Neural Networks |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Generalized Distance Bribery |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Generalized Planning via Abstraction: Arbitrary Numbers of Objects |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Generating Character Descriptions for Automatic Summarization of Fiction |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Generating Chinese Ci with Designated Metrical Structure |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Generating Distractors for Reading Comprehension Questions from Real Examinations |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Generating Live Soccer-Match Commentary from Play Data |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| Generating Multiple Diverse Responses for Short-Text Conversation |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
3 |
| Generation of Policy-Level Explanations for Reinforcement Learning |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| GeniePath: Graph Neural Networks with Adaptive Receptive Paths |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Geometric Hawkes Processes with Graph Convolutional Recurrent Neural Networks |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Geometry-Aware Face Completion and Editing |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| GlobalTrait: Personality Alignment of Multilingual Word Embeddings |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Goal-Oriented Dialogue Policy Learning from Failures |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Gradient Harmonized Single-Stage Detector |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Gradient-Based Inference for Networks with Output Constraints |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Granger-Causal Attentive Mixtures of Experts: Learning Important Features with Neural Networks |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Graph Based Translation Memory for Neural Machine Translation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Graph CNNs with Motif and Variable Temporal Block for Skeleton-Based Action Recognition |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Graph Convolutional Networks Meet Markov Random Fields: Semi-Supervised Community Detection in Attribute Networks |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Graph Convolutional Networks for Text Classification |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Greedy Maximization of Functions with Bounded Curvature under Partition Matroid Constraints |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
❌ |
4 |
| Group Decision Diagram (GDD): A Compact Representation for Permutations |
✅ |
✅ |
❌ |
❌ |
✅ |
✅ |
✅ |
5 |
| Group Fairness for the Allocation of Indivisible Goods |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Guided Dropout |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Guiding the One-to-One Mapping in CycleGAN via Optimal Transport |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| HAS-QA: Hierarchical Answer Spans Model for Open-Domain Question Answering |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| HERS: Modeling Influential Contexts with Heterogeneous Relations for Sparse and Cold-Start Recommendation |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| HSME: Hypersphere Manifold Embedding for Visible Thermal Person Re-Identification |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Hashtag Recommendation for Photo Sharing Services |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Heterogeneous Transfer Learning via Deep Matrix Completion with Adversarial Kernel Embedding |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Heuristic Search Algorithm for Dimensionality Reduction Optimally Combining Feature Selection and Feature Extraction |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Heuristic Voting as Ordinal Dominance Strategies |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Hierarchical Attention Network for Image Captioning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Hierarchical Attention Networks for Sentence Ordering |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Hierarchical Classification Based on Label Distribution Learning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Hierarchical Context Enabled Recurrent Neural Network for Recommendation |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Hierarchical Encoder with Auxiliary Supervision for Neural Table-to-Text Generation: Learning Better Representation for Tables |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Hierarchical Macro Strategy Model for MOBA Game AI |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Hierarchical Photo-Scene Encoder for Album Storytelling |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Hierarchical Reinforcement Learning for Course Recommendation in MOOCs |
✅ |
✅ |
❌ |
❌ |
✅ |
❌ |
✅ |
4 |
| Hierarchically Structured Reinforcement Learning for Topically Coherent Visual Story Generation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| High Dimensional Clustering with r-nets |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| HireNet: A Hierarchical Attention Model for the Automatic Analysis of Asynchronous Video Job Interviews |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
1 |
| Holographic Factorization Machines for Recommendation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Horizontal Pyramid Matching for Person Re-Identification |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Hotels-50K: A Global Hotel Recognition Dataset |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| How Does Knowledge of the AUC Constrain the Set of Possible Ground-Truth Labelings? |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| How Many Pairwise Preferences Do We Need to Rank a Graph Consistently? |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| How Similar Are Two Elections? |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| How to Combine Tree-Search Methods in Reinforcement Learning |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Human Action Transfer Based on 3D Model Reconstruction |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Human Motion Prediction via Learning Local Structure Representations and Temporal Dependencies |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Human-Like Delicate Region Erasing Strategy for Weakly Supervised Detection |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Human-Like Sketch Object Recognition via Analogical Learning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Human-in-the-Loop Feature Selection |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Hybrid Reinforcement Learning with Expert State Sequences |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| HyperAdam: A Learnable Task-Adaptive Adam for Network Training |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Hyperbolic Heterogeneous Information Network Embedding |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Hypergraph Neural Networks |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Hypergraph Optimization for Multi-Structural Geometric Model Fitting |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Hyperprior Induced Unsupervised Disentanglement of Latent Representations |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| I Know the Relationships: Zero-Shot Action Recognition via Two-Stream Graph Convolutional Networks and Knowledge Graphs |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| IPOMDP-Net: A Deep Neural Network for Partially Observable Multi-Agent Planning Using Interactive POMDPs |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Identification of Causal Effects in the Presence of Selection Bias |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Image Aesthetic Assessment Assisted by Attributes through Adversarial Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Image Block Augmentation for One-Shot Learning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Image Saliency Prediction in Transformed Domain: A Deep Complex Neural Network Method |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Implanting Rational Knowledge into Distributed Representation at Morpheme Level |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Implicit Argument Prediction as Reading Comprehension |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Improved Knowledge Graph Embedding Using Background Taxonomic Information |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| Improving Distantly Supervised Relation Extraction with Neural Noise Converter and Conditional Optimal Selector |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Improving Domain-Independent Planning via Critical Section Macro-Operators |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Improving Domain-Specific Classification by Collaborative Learning with Adaptation Networks |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Improving GAN with Neighbors Embedding and Gradient Matching |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Improving Hypernymy Prediction via Taxonomy Enhanced Adversarial Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Improving Image Captioning with Conditional Generative Adversarial Nets |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Improving Natural Language Inference Using External Knowledge in the Science Questions Domain |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Improving Neural Question Generation Using Answer Separation |
❌ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
5 |
| Improving One-Class Collaborative Filtering via Ranking-Based Implicit Regularizer |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Improving Optimization Bounds Using Machine Learning: Decision Diagrams Meet Deep Reinforcement Learning |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
5 |
| Improving Search with Supervised Learning in Trick-Based Card Games |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Incomplete Label Multi-Task Deep Learning for Spatio-Temporal Event Subtype Forecasting |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Incorporating Behavioral Constraints in Online AI Systems |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Incorporating Network Embedding into Markov Random Field for Better Community Detection |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Incorporating Semantic Similarity with Geographic Correlation for Query-POI Relevance Learning |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Incorporating Structured Commonsense Knowledge in Story Completion |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Induction of Non-Monotonic Logic Programs to Explain Boosted Tree Models Using LIME |
✅ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
6 |
| InfoVAE: Balancing Learning and Inference in Variational Autoencoders |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Instance-Level Facial Attributes Transfer with Geometry-Aware Flow |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Insufficient Data Can Also Rock! Learning to Converse Using Smaller Data with Augmentation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Inter-Class Angular Loss for Convolutional Neural Networks |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Interaction-Aware Factorization Machines for Recommender Systems |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Interactive Attention Transfer Network for Cross-Domain Sentiment Classification |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Interactive Semantic Parsing for If-Then Recipes via Hierarchical Reinforcement Learning |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Interleave Variational Optimization with Monte Carlo Sampling: A Tale of Two Approximate Inference Paradigms |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Interpretable Predictive Modeling for Climate Variables with Weighted Lasso |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Interpretable Preference Learning: A Game Theoretic Framework for Large Margin On-Line Feature and Rule Learning |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Interpretation of Neural Networks Is Fragile |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Interpreting Deep Models for Text Analysis via Optimization and Regularization Methods |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Inverse Abstraction of Neural Networks Using Symbolic Interpolation |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
3 |
| Iterated Belief Base Revision: A Dynamic Epistemic Logic Approach |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Iterative Classroom Teaching |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Joint Dynamic Pose Image and Space Time Reversal for Human Action Recognition from Videos |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Joint Extraction of Entities and Overlapping Relations Using Position-Attentive Sequence Labeling |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Joint Representation Learning for Multi-Modal Transportation Recommendation |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Joint Semi-Supervised Feature Selection and Classification through Bayesian Approach |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Jointly Extracting Multiple Triplets with Multilayer Translation Constraints |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Jointly Learning to Label Sentences and Tokens |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| KVQA: Knowledge-Aware Visual Question Answering |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Kernelized Hashcode Representations for Relation Extraction |
✅ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
6 |
| Knowledge Distillation with Adversarial Samples Supporting Decision Boundary |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Knowledge Refinement via Rule Selection |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Knowledge-Driven Encode, Retrieve, Paraphrase for Medical Image Report Generation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| LENA: Locality-Expanded Neural Embedding for Knowledge Base Completion |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Label Embedding with Partial Heterogeneous Contexts |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| LabelForest: Non-Parametric Semi-Supervised Learning for Activity Recognition |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
3 |
| Large Scale Learning of Agent Rationality in Two-Player Zero-Sum Games |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Large-Scale Heterogeneous Feature Embedding |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Large-Scale Interactive Recommendation with Tree-Structured Policy Gradient |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Large-Scale Visual Relationship Understanding |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Latent Dirichlet Allocation for Internet Price War |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Latent Multi-Task Architecture Learning |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Lattice CNNs for Matching Based Chinese Question Answering |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Learning (from) Deep Hierarchical Structure among Features |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning Adaptive Random Features |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning Anytime Predictions in Neural Networks via Adaptive Loss Balancing |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning Attribute-Specific Representations for Visual Tracking |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Learning Basis Representation to Refine 3D Human Pose Estimations |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Learning Compact Model for Large-Scale Multi-Label Data |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Learning Competitive and Discriminative Reconstructions for Anomaly Detection |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Learning Deviation Payoffs in Simulation-Based Games |
✅ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning Diffusions without Timestamps |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Learning Disentangled Representation with Pairwise Independence |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning Diverse Bayesian Networks |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
3 |
| Learning Dynamic Generator Model by Alternating Back-Propagation through Time |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Learning Features and Abstract Actions for Computing Generalized Plans |
❌ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
3 |
| Learning Fully Dense Neural Networks for Image Semantic Segmentation |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Learning Heterogeneous Spatial-Temporal Representation for Bike-Sharing Demand Prediction |
✅ |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
5 |
| Learning How to Ground a Plan – Partial Grounding in Classical Planning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| Learning Incremental Triplet Margin for Person Re-Identification |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Learning Logistic Circuits |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Learning Models of Sequential Decision-Making with Partial Specification of Agent Behavior |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Learning Multi-Task Communication with Message Passing for Sequence Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning Neural Bag-of-Matrix-Summarization with Riemannian Network |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Learning Non-Uniform Hypergraph for Multi-Object Tracking |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Learning Object Context for Dense Captioning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning Optimal Classification Trees Using a Binary Linear Program Formulation |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
6 |
| Learning Optimal Strategies to Commit To |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making |
❌ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
5 |
| Learning Personalized Attribute Preference via Multi-Task AUC Optimization |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| Learning Personalized End-to-End Goal-Oriented Dialog |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Learning Phenotypes and Dynamic Patient Representations via RNN Regularized Collective Non-Negative Tensor Factorization |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Learning Plackett-Luce Mixtures from Partial Preferences |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Learning Resolution-Invariant Deep Representations for Person Re-Identification |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Learning Resource Allocation and Pricing for Cloud Profit Maximization |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Learning Segmentation Masks with the Independence Prior |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Learning Semantic Representations for Novel Words: Leveraging Both Form and Context |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning Set Functions with Limited Complementarity |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Learning Transferable Self-Attentive Representations for Action Recognition in Untrimmed Videos with Weak Supervision |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning Triggers for Heterogeneous Treatment Effects |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Learning Uniform Semantic Features for Natural Language and Programming Language Globally, Locally and Sequentially |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Learning Vine Copula Models for Synthetic Data Generation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Learning a Deep Convolutional Network for Colorization in Monochrome-Color Dual-Lens System |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Learning a Key-Value Memory Co-Attention Matching Network for Person Re-Identification |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Learning a Visual Tracker from a Single Movie without Annotation |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Learning from Web Data Using Adversarial Discriminative Neural Networks for Fine-Grained Classification |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Learning to Adaptively Scale Recurrent Neural Networks |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning to Address Health Inequality in the United States with a Bayesian Decision Network |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
✅ |
4 |
| Learning to Align Question and Answer Utterances in Customer Service Conversation with Recurrent Pointer Networks |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Learning to Communicate and Solve Visual Blocks-World Tasks |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Learning to Compose Topic-Aware Mixture of Experts for Zero-Shot Video Captioning |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Learning to Embed Sentences Using Attentive Recursive Trees |
✅ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
6 |
| Learning to Localize Objects with Noisy Labeled Instances |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning to Solve NP-Complete Problems: A Graph Neural Network for Decision TSP |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Learning to Steer by Mimicking Features from Heterogeneous Auxiliary Networks |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning to Teach in Cooperative Multiagent Reinforcement Learning |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Learning to Write Stories with Thematic Consistency and Wording Novelty |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Less but Better: Generalization Enhancement of Ordinal Embedding via Distributional Margin |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Leveraging Observations in Bandits: Between Risks and Benefits |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Leveraging Web Semantic Knowledge in Word Representation Learning |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Lifelong Path Planning with Kinematic Constraints for Multi-Agent Pickup and Delivery |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Lifted Hinge-Loss Markov Random Fields |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
❌ |
3 |
| Lifted Proximal Operator Machines |
✅ |
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✅ |
❌ |
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✅ |
3 |
| Linear Kernel Tests via Empirical Likelihood for High-Dimensional Data |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Lipper: Synthesizing Thy Speech Using Multi-View Lipreading |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| LiveBot: Generating Live Video Comments Based on Visual and Textual Contexts |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Localizing Natural Language in Videos |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph Embedding |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Long Short-Term Memory with Dynamic Skip Connections |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Look across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| Low-Distortion Social Welfare Functions |
❌ |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
1 |
| Low-Rank Semidefinite Programming for the MAX2SAT Problem |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| M2Det: A Single-Shot Object Detector Based on Multi-Level Feature Pyramid Network |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
✅ |
6 |
| MEAL: Multi-Model Ensemble via Adversarial Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| MFBO-SSM: Multi-Fidelity Bayesian Optimization for Fast Inference in State-Space Models |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| MFPCA: Multiscale Functional Principal Component Analysis |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| MLVCNN: Multi-Loop-View Convolutional Neural Network for 3D Shape Retrieval |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| MNCN: A Multilingual Ngram-Based Convolutional Network for Aspect Category Detection in Online Reviews |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| MPD-AL: An Efficient Membrane Potential Driven Aggregate-Label Learning Algorithm for Spiking Neurons |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| MR-NET: Exploiting Mutual Relation for Visual Relationship Detection |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| MVPNet: Multi-View Point Regression Networks for 3D Object Reconstruction from A Single Image |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Making Money from What You Know – How to Sell Information? |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Manifold-Valued Image Generation with Wasserstein Generative Adversarial Nets |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Marginal Inference in Continuous Markov Random Fields Using Mixtures |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Matrix Completion for Graph-Based Deep Semi-Supervised Learning |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Measurement Maximizing Adaptive Sampling with Risk Bounding Functions |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Mechanism Design for Multi-Type Housing Markets with Acceptable Bundles |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Meimei: An Efficient Probabilistic Approach for Semantically Annotating Tables |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Memory Bounded Open-Loop Planning in Large POMDPs Using Thompson Sampling |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Memory-Augmented Temporal Dynamic Learning for Action Recognition |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| MeshNet: Mesh Neural Network for 3D Shape Representation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Message-Dropout: An Efficient Training Method for Multi-Agent Deep Reinforcement Learning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Meta Learning for Image Captioning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Meta-Descent for Online, Continual Prediction |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| MetaStyle: Three-Way Trade-off among Speed, Flexibility, and Quality in Neural Style Transfer |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Migration as Submodular Optimization |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
3 |
| Minimum Intervention Cover of a Causal Graph |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Mining Entity Synonyms with Efficient Neural Set Generation |
✅ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
6 |
| Mirroring without Overimitation: Learning Functionally Equivalent Manipulation Actions |
❌ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
2 |
| MixUp as Locally Linear Out-of-Manifold Regularization |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Mixture of Expert/Imitator Networks: Scalable Semi-Supervised Learning Framework |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Mode Variational LSTM Robust to Unseen Modes of Variation: Application to Facial Expression Recognition |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Model Learning for Look-Ahead Exploration in Continuous Control |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
3 |
| Model-Based Diagnosis for Cyber-Physical Production Systems Based on Machine Learning and Residual-Based Diagnosis Models |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Model-Based Diagnosis of Hybrid Systems Using Satisfiability Modulo Theory |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Model-Free IRL Using Maximum Likelihood Estimation |
✅ |
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✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Modeling Coherence for Discourse Neural Machine Translation |
❌ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
5 |
| Modeling Local Dependence in Natural Language with Multi-Channel Recurrent Neural Networks |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Modelling Autobiographical Memory Loss across Life Span |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Modelling of Bi-Directional Spatio-Temporal Dependence and Users’ Dynamic Preferences for Missing POI Check-In Identification |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Modular Materialisation of Datalog Programs |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Molecular Property Prediction: A Multilevel Quantum Interactions Modeling Perspective |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Mono3D++: Monocular 3D Vehicle Detection with Two-Scale 3D Hypotheses and Task Priors |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Moral Permissibility of Action Plans |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Motion Guided Spatial Attention for Video Captioning |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| MotionTransformer: Transferring Neural Inertial Tracking between Domains |
❌ |
❌ |
✅ |
✅ |
❌ |
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3 |
| Multi-Agent Discussion Mechanism for Natural Language Generation |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Multi-Agent Path Finding for Large Agents |
✅ |
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✅ |
❌ |
✅ |
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4 |
| Multi-Attribute Transfer via Disentangled Representation |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
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3 |
| Multi-Context System for Optimization Problems |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Multi-Dimensional Classification via kNN Feature Augmentation |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Multi-Fidelity Automatic Hyper-Parameter Tuning via Transfer Series Expansion |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Multi-GCN: Graph Convolutional Networks for Multi-View Networks, with Applications to Global Poverty |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Multi-Interactive Memory Network for Aspect Based Multimodal Sentiment Analysis |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Multi-Labeled Relation Extraction with Attentive Capsule Network |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Multi-Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Multi-Matching Network for Multiple Choice Reading Comprehension |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
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4 |
| Multi-Order Attentive Ranking Model for Sequential Recommendation |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
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4 |
| Multi-Perspective Relevance Matching with Hierarchical ConvNets for Social Media Search |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Multi-Precision Quantized Neural Networks via Encoding Decomposition of {-1,+1} |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Multi-Scale 3D Convolution Network for Video Based Person Re-Identification |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Multi-Source Neural Variational Inference |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Multi-Task Deep Reinforcement Learning with PopArt |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question Answering |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Multi-Unit Bilateral Trade |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Multi-View Anomaly Detection: Neighborhood in Locality Matters |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Multi-View Information-Theoretic Co-Clustering for Co-Occurrence Data |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Multi-View Multi-Instance Multi-Label Learning Based on Collaborative Matrix Factorization |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Multi-Winner Contests for Strategic Diffusion in Social Networks |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Multi3Net: Segmenting Flooded Buildings via Fusion of Multiresolution, Multisensor, and Multitemporal Satellite Imagery |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
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3 |
| Multiagent Decision Making For Maritime Traffic Management |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Multigrid Backprojection Super–Resolution and Deep Filter Visualization |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Multilevel Language and Vision Integration for Text-to-Clip Retrieval |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Multiple Independent Subspace Clusterings |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Multiple Saliency and Channel Sensitivity Network for Aggregated Convolutional Feature |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Multistream Classification with Relative Density Ratio Estimation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Natural Option Critic |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| NeVAE: A Deep Generative Model for Molecular Graphs |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Near-Lossless Binarization of Word Embeddings |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Near-Neighbor Methods in Random Preference Completion |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Nearest-Neighbour-Induced Isolation Similarity and Its Impact on Density-Based Clustering |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Network Recasting: A Universal Method for Network Architecture Transformation |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Network Structure and Transfer Behaviors Embedding via Deep Prediction Model |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Neural Collective Graphical Models for Estimating Spatio-Temporal Population Flow from Aggregated Data |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Neural Machine Translation with Adequacy-Oriented Learning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Neural Relation Extraction within and across Sentence Boundaries |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Neural Speech Synthesis with Transformer Network |
❌ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
2 |
| No-Reference Image Quality Assessment with Reinforcement Recursive List-Wise Ranking |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Non-Asymptotic Uniform Rates of Consistency for k-NN Regression |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Non-Autoregressive Machine Translation with Auxiliary Regularization |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Non-Compensatory Psychological Models for Recommender Systems |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Non-Ergodic Convergence Analysis of Heavy-Ball Algorithms |
❌ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
2 |
| Non-Local Context Encoder: Robust Biomedical Image Segmentation against Adversarial Attacks |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
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4 |
| Non-Parametric Transformation Networks for Learning General Invariances from Data |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Number Sequence Prediction Problems for Evaluating Computational Powers of Neural Networks |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Object Detection Based on Region Decomposition and Assembly |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
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4 |
| Object Reachability via Swaps along a Line |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| On Completing Sparse Knowledge Base with Transitive Relation Embedding |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| On Fair Cost Sharing Games in Machine Learning |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| On Geometric Alignment in Low Doubling Dimension |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| On Lifted Inference Using Neural Embeddings |
✅ |
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❌ |
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3 |
| On Limited Conjunctions and Partial Features in Parameter-Tractable Feature Logics |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| On Rational Delegations in Liquid Democracy |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| On Reinforcement Learning for Full-Length Game of StarCraft |
✅ |
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✅ |
3 |
| On Resolving Ambiguous Anaphoric Expressions in Imperative Discourse |
✅ |
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❌ |
✅ |
2 |
| On Sampling Complexity of the Semidefinite Affine Rank Feasibility Problem |
✅ |
❌ |
❌ |
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❌ |
✅ |
2 |
| On Strength Adjustment for MCTS-Based Programs |
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❌ |
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✅ |
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✅ |
2 |
| On Structured Argumentation with Conditional Preferences |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| On Testing of Uniform Samplers |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| On the Complexity of the Inverse Semivalue Problem for Weighted Voting Games |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| On the Distortion Value of the Elections with Abstention |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| On the Hardness of Probabilistic Inference Relaxations |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| On the Inducibility of Stackelberg Equilibrium for Security Games |
❌ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
3 |
| On the Optimal Efficiency of Cost-Algebraic A* |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| On the Persistence of Clustering Solutions and True Number of Clusters in a Dataset |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| On the Proximity of Markets with Integral Equilibria |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| On the Time Complexity of Algorithm Selection Hyper-Heuristics for Multimodal Optimisation |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| On-Line Adaptative Curriculum Learning for GANs |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| On-Line Learning of Linear Dynamical Systems: Exponential Forgetting in Kalman Filters |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
3 |
| One for All: Neural Joint Modeling of Entities and Events |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| One-Class Adversarial Nets for Fraud Detection |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| One-Network Adversarial Fairness |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| One-Pass Incomplete Multi-View Clustering |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Online Convex Optimization for Sequential Decision Processes and Extensive-Form Games |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Online Embedding Compression for Text Classification Using Low Rank Matrix Factorization |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Online Learning from Data Streams with Varying Feature Spaces |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Online Multi-Agent Pathfinding |
✅ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
4 |
| Online Pandora’s Boxes and Bandits |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Ontology-Based Query Answering for Probabilistic Temporal Data |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Ontology-Mediated Query Answering over Log-Linear Probabilistic Data |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Operator Mutexes and Symmetries for Simplifying Planning Tasks |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Optimal Dynamic Auctions Are Virtual Welfare Maximizers |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Optimal Interdiction of Urban Criminals with the Aid of Real-Time Information |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Optimal Projection Guided Transfer Hashing for Image Retrieval |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Optimal Surveillance of Covert Networks by Minimizing Inverse Geodesic Length |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Optimization of Hierarchical Regression Model with Application to Optimizing Multi-Response Regression K-ary Trees |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Optimizing Discount and Reputation Trade-Offs in E-Commerce Systems: Characterization and Online Learning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Optimizing in the Dark: Learning an Optimal Solution through a Simple Request Interface |
✅ |
❌ |
✅ |
❌ |
❌ |
✅ |
✅ |
4 |
| Orderly Subspace Clustering |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Orthogonality-Promoting Dictionary Learning via Bayesian Inference |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Outlier Aware Network Embedding for Attributed Networks |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Overcoming Blind Spots in the Real World: Leveraging Complementary Abilities for Joint Execution |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
1 |
| Oversampling for Imbalanced Data via Optimal Transport |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| PARABANK: Monolingual Bitext Generation and Sentential Paraphrasing via Lexically-Constrained Neural Machine Translation |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| PCGAN: Partition-Controlled Human Image Generation |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| PGANs: Personalized Generative Adversarial Networks for ECG Synthesis to Improve Patient-Specific Deep ECG Classification |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| PVRNet: Point-View Relation Neural Network for 3D Shape Recognition |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Paraphrase Diversification Using Counterfactual Debiasing |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Pareto Efficient Auctions with Interest Rates |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Pareto Optimal Allocation under Compact Uncertain Preferences |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Pareto Optimization for Subset Selection with Dynamic Cost Constraints |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Pareto-Optimal Allocation of Indivisible Goods with Connectivity Constraints |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Partial Awareness |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Partial Label Learning via Label Enhancement |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Partial Label Learning with Self-Guided Retraining |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Partial Multi-Label Learning by Low-Rank and Sparse Decomposition |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Partial Multi-Label Learning via Credible Label Elicitation |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Partial Verification as a Substitute for Money |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Partially Observable Multi-Sensor Sequential Change Detection: A Combinatorial Multi-Armed Bandit Approach |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Path-Specific Counterfactual Fairness |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Pathological Evidence Exploration in Deep Retinal Image Diagnosis |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Perceptual Pyramid Adversarial Networks for Text-to-Image Synthesis |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Perceptual-Sensitive GAN for Generating Adversarial Patches |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Performance Guarantees for Homomorphisms beyond Markov Decision Processes |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| PerformanceNet: Score-to-Audio Music Generation with Multi-Band Convolutional Residual Network |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Personalized Question Routing via Heterogeneous Network Embedding |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Personalized Robot Tutoring Using the Assistive Tutor POMDP (AT-POMDP) |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| PhoneMD: Learning to Diagnose Parkinson’s Disease from Smartphone Data |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Plan-Length Bounds: Beyond 1-Way Dependency |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Plan-and-Write: Towards Better Automatic Storytelling |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Play as You Like: Timbre-Enhanced Multi-Modal Music Style Transfer |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Point Cloud Processing via Recurrent Set Encoding |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Point2Sequence: Learning the Shape Representation of 3D Point Clouds with an Attention-Based Sequence to Sequence Network |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Policy Optimization with Model-Based Explorations |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Poll-Confident Voters in Iterative Voting |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Polynomial-Time Probabilistic Reasoning with Partial Observations via Implicit Learning in Probability Logics |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Popularity Prediction on Online Articles with Deep Fusion of Temporal Process and Content Features |
❌ |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
3 |
| Practical Algorithms for Multi-Stage Voting Rules with Parallel Universes Tiebreaking |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Precision-Recall versus Accuracy and the Role of Large Data Sets |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Predicting Concrete and Abstract Entities in Modern Poetry |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Predicting Hurricane Trajectories Using a Recurrent Neural Network |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Predicting Urban Dispersal Events: A Two-Stage Framework through Deep Survival Analysis on Mobility Data |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Predicting and Analyzing Language Specificity in Social Media Posts |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Predicting the Argumenthood of English Prepositional Phrases |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Preference-Aware Task Assignment in On-Demand Taxi Dispatching: An Online Stable Matching Approach |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
3 |
| Preference-Aware Task Assignment in Spatial Crowdsourcing |
❌ |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
3 |
| Primarily about Primaries |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Private Model Compression via Knowledge Distillation |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Probabilistic Alternating-Timeµ-Calculus |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Probabilistic Logic Programming with Beta-Distributed Random Variables |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Probabilistic Model Checking of Robots Deployed in Extreme Environments |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Projection Convolutional Neural Networks for 1-bit CNNs via Discrete Back Propagation |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| QUAREL: A Dataset and Models for Answering Questions about Qualitative Relationships |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| QUOTA: The Quantile Option Architecture for Reinforcement Learning |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Qualitative Spatial Logic over 2D Euclidean Spaces Is Not Finitely Axiomatisable |
❌ |
❌ |
❌ |
❌ |
✅ |
✅ |
❌ |
2 |
| Quantifying Uncertainties in Natural Language Processing Tasks |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Quasi-Perfect Stackelberg Equilibrium |
❌ |
❌ |
❌ |
❌ |
✅ |
✅ |
❌ |
2 |
| Querying Attributed DL-Lite Ontologies Using Provenance Semirings |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| RGBD Based Gaze Estimation via Multi-Task CNN |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| RS3CIS: Robust Single-Step Spectral Clustering with Intrinsic Subspace |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Random Dictators with a Random Referee: Constant Sample Complexity Mechanisms for Social Choice |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Random Feature Maps for the Itemset Kernel |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Random Walk Decay Centrality |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Randomized Strategies for Robust Combinatorial Optimization |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Randomized Wagering Mechanisms |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Ranking-Based Deep Cross-Modal Hashing |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Re-Evaluating ADEM: A Deeper Look at Scoring Dialogue Responses |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Re2EMA: Regularized and Reinitialized Exponential Moving Average for Target Model Update in Object Tracking |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| ReAl-LiFE: Accelerating the Discovery of Individualized Brain Connectomes on GPUs |
✅ |
✅ |
✅ |
✅ |
✅ |
✅ |
✅ |
7 |
| Read + Verify: Machine Reading Comprehension with Unanswerable Questions |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in Videos |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Real-Time Planning as Decision-Making under Uncertainty |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Reasoning over Assumption-Based Argumentation Frameworks via Direct Answer Set Programming Encodings |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Reasoning over Streaming Data in Metric Temporal Datalog |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Recognizing Unseen Attribute-Object Pair with Generative Model |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Recurrent Attention Model for Pedestrian Attribute Recognition |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Recurrent Poisson Process Unit for Speech Recognition |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Recurrent Stacking of Layers for Compact Neural Machine Translation Models |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
5 |
| Recursively Learning Causal Structures Using Regression-Based Conditional Independence Test |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Red-Black Heuristics for Planning Tasks with Conditional Effects |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Refining Abstraction Heuristics during Real-Time Planning |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Refining Coarse-Grained Spatial Data Using Auxiliary Spatial Data Sets with Various Granularities |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Region-Based Message Exploration over Spatio-Temporal Data Streams |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Regular Boardgames |
❌ |
✅ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Regularized Evolution for Image Classifier Architecture Search |
✅ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
6 |
| Regularizing Neural Machine Translation by Target-Bidirectional Agreement |
✅ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
6 |
| Relation Structure-Aware Heterogeneous Information Network Embedding |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Relaxing and Restraining Queries for OBDA |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| RepeatNet: A Repeat Aware Neural Recommendation Machine for Session-Based Recommendation |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Representing and Learning Grammars in Answer Set Programming |
❌ |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
1 |
| Residual Attribute Attention Network for Face Image Super-Resolution |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Residual Compensation Networks for Heterogeneous Face Recognition |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Residual Invertible Spatio-Temporal Network for Video Super-Resolution |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Resisting Adversarial Attacks Using Gaussian Mixture Variational Autoencoders |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Response Generation by Context-Aware Prototype Editing |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| Rethinking the Discount Factor in Reinforcement Learning: A Decision Theoretic Approach |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Revenue Enhancement via Asymmetric Signaling in Interdependent-Value Auctions |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Reverse-Engineering Satire, or “Paper on Computational Humor Accepted despite Making Serious Advances” |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Revisiting LSTM Networks for Semi-Supervised Text Classification via Mixed Objective Function |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Revisiting Projection-Free Optimization for Strongly Convex Constraint Sets |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Robust Anomaly Detection in Videos Using Multilevel Representations |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Robust Deep Co-Saliency Detection with Group Semantic |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Robust Estimation of Similarity Transformation for Visual Object Tracking |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Robust Metric Learning on Grassmann Manifolds with Generalization Guarantees |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Robust Negative Sampling for Network Embedding |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Robust Online Matching with User Arrival Distribution Drift |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Robust Optimization over Multiple Domains |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Robust Ordinal Embedding from Contaminated Relative Comparisons |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Robustness Can Be Cheap: A Highly Efficient Approach to Discover Outliers under High Outlier Ratios |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
✅ |
5 |
| Robustness Envelopes for Temporal Plans |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Robustness Guarantees for Bayesian Inference with Gaussian Processes |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Rotational Diversity in Multi-Cycle Assignment Problems |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
✅ |
2 |
| Running Time Analysis of MOEA/D with Crossover on Discrete Optimization Problem |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| SADIH: Semantic-Aware DIscrete Hashing |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| SAFE: A Neural Survival Analysis Model for Fraud Early Detection |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| SAM-Net: Integrating Event-Level and Chain-Level Attentions to Predict What Happens Next |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| SAT-Based Explicit LTLf Satisfiability Checking |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
6 |
| SCFont: Structure-Guided Chinese Font Generation via Deep Stacked Networks |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| SCNN: A General Distribution Based Statistical Convolutional Neural Network with Application to Video Object Detection |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| SDRL: Interpretable and Data-Efficient Deep Reinforcement Learning Leveraging Symbolic Planning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| SEGAN: Structure-Enhanced Generative Adversarial Network for Compressed Sensing MRI Reconstruction |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-Task Learning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| STA: Spatial-Temporal Attention for Large-Scale Video-Based Person Re-Identification |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| SVM-Based Deep Stacking Networks |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Safe Partial Diagnosis from Normal Observations |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Safe Policy Improvement with Baseline Bootstrapping in Factored Environments |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Safeguarded Dynamic Label Regression for Noisy Supervision |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Satisfiability in Strategy Logic Can Be Easier than Model Checking |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Scalable Distributed DL Training: Batching Communication and Computation |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Scalable Recollections for Continual Lifelong Learning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Scalable Robust Kidney Exchange |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
✅ |
4 |
| Scalable and Efficient Pairwise Learning to Achieve Statistical Accuracy |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Scale Invariant Fully Convolutional Network: Detecting Hands Efficiently |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Scaling-Up Split-Merge MCMC with Locality Sensitive Sampling (LSS) |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Scene Text Detection with Supervised Pyramid Context Network |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Scene Text Recognition from Two-Dimensional Perspective |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| ScisummNet: A Large Annotated Corpus and Content-Impact Models for Scientific Paper Summarization with Citation Networks |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Searching with Consistent Prioritization for Multi-Agent Path Finding |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Segregated Temporal Assembly Recurrent Networks for Weakly Supervised Multiple Action Detection |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Selecting Compliant Agents for Opt-in Micro-Tolling |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Selective Refinement Network for High Performance Face Detection |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Self-Adversarially Learned Bayesian Sampling |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Self-Ensembling Attention Networks: Addressing Domain Shift for Semantic Segmentation |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Self-Paced Active Learning: Query the Right Thing at the Right Time |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Self-Supervised Mixture-of-Experts by Uncertainty Estimation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Self-Supervised Video Representation Learning with Space-Time Cubic Puzzles |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Semantic Adversarial Network with Multi-Scale Pyramid Attention for Video Classification |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Semantic Proposal for Activity Localization in Videos via Sentence Query |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Semantic Relationships Guided Representation Learning for Facial Action Unit Recognition |
❌ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
5 |
| Semantic Sentence Matching with Densely-Connected Recurrent and Co-Attentive Information |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Semi-Parametric Sampling for Stochastic Bandits with Many Arms |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Sensitivity Analysis of Deep Neural Networks |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Sentence-Wise Smooth Regularization for Sequence to Sequence Learning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| SepNE: Bringing Separability to Network Embedding |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Separator-Based Pruned Dynamic Programming for Steiner Tree |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
6 |
| Session-Based Recommendation with Graph Neural Networks |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Sign-Full Random Projections |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Similarity Learning via Kernel Preserving Embedding |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Similarity Preserving Deep Asymmetric Quantization for Image Retrieval |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Simulation-Based Approach to Efficient Commonsense Reasoning in Very Large Knowledge Bases |
✅ |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
4 |
| Singe Image Rain Removal with Unpaired Information: A Differentiable Programming Perspective |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Single-Label Multi-Class Image Classification by Deep Logistic Regression |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Skeleton-Based Gesture Recognition Using Several Fully Connected Layers with Path Signature Features and Temporal Transformer Module |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Sliding Window Temporal Graph Coloring |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Smooth Deep Image Generator from Noises |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Soft Facial Landmark Detection by Label Distribution Learning |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Solving Imperfect-Information Games via Discounted Regret Minimization |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Solving Integer Quadratic Programming via Explicit and Structural Restrictions |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Solving Large Extensive-Form Games with Strategy Constraints |
✅ |
❌ |
✅ |
❌ |
❌ |
✅ |
✅ |
4 |
| Solving Multiagent Planning Problems with Concurrent Conditional Effects |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Solving Partially Observable Stochastic Games with Public Observations |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| SpHMC: Spectral Hamiltonian Monte Carlo |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Sparse Adversarial Perturbations for Videos |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Sparse Reject Option Classifier Using Successive Linear Programming |
✅ |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
5 |
| Spatial Mixture Models with Learnable Deep Priors for Perceptual Grouping |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Spatial and Temporal Mutual Promotion for Video-Based Person Re-Identification |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Spatial-Temporal Person Re-Identification |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Spatiality Preservable Factored Poisson Regression for Large-Scale Fine-Grained GPS-Based Population Analysis |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
1 |
| Spatially Invariant Unsupervised Object Detection with Convolutional Neural Networks |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| Spatio-Temporal Graph Routing for Skeleton-Based Action Recognition |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Spectral Clustering in Heterogeneous Information Networks |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Spell Once, Summon Anywhere: A Two-Level Open-Vocabulary Language Model |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| StNet: Local and Global Spatial-Temporal Modeling for Action Recognition |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| State Abstraction as Compression in Apprenticeship Learning |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| State-Augmentation Transformations for Risk-Sensitive Reinforcement Learning |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Stepping Stones to Inductive Synthesis of Low-Level Looping Programs |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Stochastic Submodular Maximization with Performance-Dependent Item Costs |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Story Ending Generation with Incremental Encoding and Commonsense Knowledge |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Strong Equivalence for Epistemic Logic Programs Made Easy |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Structural Causal Bandits with Non-Manipulable Variables |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Structured Bayesian Networks: From Inference to Learning with Routes |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Structured Two-Stream Attention Network for Video Question Answering |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Structured and Sparse Annotations for Image Emotion Distribution Learning |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Sublinear Time Numerical Linear Algebra for Structured Matrices |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Submodular Optimization over Streams with Inhomogeneous Decays |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Subspace Selection via DR-Submodular Maximization on Lattices |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Subtask Gated Networks for Non-Intrusive Load Monitoring |
❌ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
4 |
| Successor Features Based Multi-Agent RL for Event-Based Decentralized MDPs |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Super Sparse Convolutional Neural Networks |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| SuperVAE: Superpixelwise Variational Autoencoder for Salient Object Detection |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Supervised User Ranking in Signed Social Networks |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Surveys without Questions: A Reinforcement Learning Approach |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
1 |
| Switch-Based Active Deep Dyna-Q: Efficient Adaptive Planning for Task-Completion Dialogue Policy Learning |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
3 |
| Switch-LSTMs for Multi-Criteria Chinese Word Segmentation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Symmetry-Breaking Constraints for Grid-Based Multi-Agent Path Finding |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Syntax-Aware Neural Semantic Role Labeling |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
5 |
| TAPAS: Train-Less Accuracy Predictor for Architecture Search |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| TDSNN: From Deep Neural Networks to Deep Spike Neural Networks with Temporal-Coding |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| TET-GAN: Text Effects Transfer via Stylization and Destylization |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| TableSense: Spreadsheet Table Detection with Convolutional Neural Networks |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Tackling Sparse Rewards in Real-Time Games with Statistical Forward Planning Methods |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Talking Face Generation by Adversarially Disentangled Audio-Visual Representation |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| TallyQA: Answering Complex Counting Questions |
❌ |
❌ |
✅ |
✅ |
❌ |
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3 |
| Task Embedded Coordinate Update: A Realizable Framework for Multivariate Non-Convex Optimization |
✅ |
❌ |
✅ |
❌ |
❌ |
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2 |
| Task Transfer by Preference-Based Cost Learning |
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❌ |
1 |
| Task-Driven Common Representation Learning via Bridge Neural Network |
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❌ |
❌ |
✅ |
4 |
| Template-Based Math Word Problem Solvers with Recursive Neural Networks |
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✅ |
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✅ |
✅ |
❌ |
✅ |
5 |
| Temporal Anomaly Detection: Calibrating the Surprise |
✅ |
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✅ |
✅ |
❌ |
✅ |
6 |
| Temporal Bilinear Networks for Video Action Recognition |
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✅ |
✅ |
❌ |
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✅ |
3 |
| Temporal Deformable Convolutional Encoder-Decoder Networks for Video Captioning |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Temporal Planning with Temporal Metric Trajectory Constraints |
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❌ |
✅ |
❌ |
✅ |
5 |
| Tensor Decomposition for Multilayer Networks Clustering |
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❌ |
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✅ |
3 |
| Tensor Ring Decomposition with Rank Minimization on Latent Space: An Efficient Approach for Tensor Completion |
✅ |
✅ |
✅ |
❌ |
❌ |
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✅ |
4 |
| Tensorial Change Analysis Using Probabilistic Tensor Regression |
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❌ |
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✅ |
4 |
| Text Assisted Insight Ranking Using Context-Aware Memory Network |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| That’s Mine! Learning Ownership Relations and Norms for Robots |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| The Adversarial Attack and Detection under the Fisher Information Metric |
✅ |
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✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| The Goldilocks Zone: Towards Better Understanding of Neural Network Loss Landscapes |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| The Kelly Growth Optimal Portfolio with Ensemble Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| The Pure Price of Anarchy of Pool Block Withholding Attacks in Bitcoin Mining |
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❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| The SpectACl of Nonconvex Clustering: A Spectral Approach to Density-Based Clustering |
✅ |
✅ |
✅ |
❌ |
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❌ |
✅ |
4 |
| The Utility of Sparse Representations for Control in Reinforcement Learning |
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❌ |
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✅ |
3 |
| Theoretical Analysis of Label Distribution Learning |
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❌ |
❌ |
❌ |
❌ |
0 |
| Theory of Minds: Understanding Behavior in Groups through Inverse Planning |
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❌ |
❌ |
✅ |
1 |
| Tied Transformers: Neural Machine Translation with Shared Encoder and Decoder |
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✅ |
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4 |
| Tile2Vec: Unsupervised Representation Learning for Spatially Distributed Data |
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✅ |
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❌ |
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4 |
| Title-Guided Encoding for Keyphrase Generation |
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✅ |
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3 |
| To Find Where You Talk: Temporal Sentence Localization in Video with Attention Based Location Regression |
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❌ |
✅ |
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❌ |
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4 |
| TopicEq: A Joint Topic and Mathematical Equation Model for Scientific Texts |
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✅ |
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❌ |
❌ |
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3 |
| Towards Automated Semi-Supervised Learning |
❌ |
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❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Towards Better Interpretability in Deep Q-Networks |
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✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Towards Highly Accurate and Stable Face Alignment for High-Resolution Videos |
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✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Towards Optimal Discrete Online Hashing with Balanced Similarity |
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❌ |
❌ |
❌ |
✅ |
3 |
| Towards Optimal Fine Grained Retrieval via Decorrelated Centralized Loss with Normalize-Scale Layer |
✅ |
❌ |
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❌ |
❌ |
❌ |
✅ |
3 |
| Towards Personalized Review Summarization via User-Aware Sequence Network |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
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3 |
| Towards Reliable Learning for High Stakes Applications |
❌ |
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✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Towards Sentence-Level Brain Decoding with Distributed Representations |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Tracking Logical Difference in Large-Scale Ontologies: A Forgetting-Based Approach |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
6 |
| Traffic Updates: Saying a Lot While Revealing a Little |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| TrafficPredict: Trajectory Prediction for Heterogeneous Traffic-Agents |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Trainable Undersampling for Class-Imbalance Learning |
✅ |
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✅ |
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❌ |
❌ |
✅ |
4 |
| Training Complex Models with Multi-Task Weak Supervision |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
4 |
| Training Deep Neural Networks in Generations: A More Tolerant Teacher Educates Better Students |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Training Temporal Word Embeddings with a Compass |
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✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| TransConv: Relationship Embedding in Social Networks |
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✅ |
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3 |
| TransGate: Knowledge Graph Embedding with Shared Gate Structure |
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✅ |
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4 |
| TransNFCM: Translation-Based Neural Fashion Compatibility Modeling |
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❌ |
✅ |
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❌ |
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✅ |
3 |
| Transductive Bounds for the Multi-Class Majority Vote Classifier |
✅ |
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✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Transfer Learning for Sequence Labeling Using Source Model and Target Data |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Transferable Attention for Domain Adaptation |
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✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Transferable Curriculum for Weakly-Supervised Domain Adaptation |
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❌ |
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3 |
| Transferable Interactive Memory Network for Domain Adaptation in Fine-Grained Opinion Extraction |
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❌ |
✅ |
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3 |
| Translating with Bilingual Topic Knowledge for Neural Machine Translation |
❌ |
❌ |
✅ |
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✅ |
❌ |
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4 |
| Triple Classification Using Regions and Fine-Grained Entity Typing |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
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5 |
| Trust Region Evolution Strategies |
✅ |
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❌ |
❌ |
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3 |
| Turbo Learning Framework for Human-Object Interactions Recognition and Human Pose Estimation |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Two-Stage Label Embedding via Neural Factorization Machine for Multi-Label Classification |
✅ |
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✅ |
❌ |
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❌ |
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4 |
| UGSD: User Generated Sentiment Dictionaries from Online Customer Reviews |
❌ |
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❌ |
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3 |
| Unbounded Orchestrations of Transducers for Manufacturing |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Uncovering Specific-Shape Graph Anomalies in Attributed Graphs |
✅ |
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❌ |
❌ |
✅ |
❌ |
❌ |
2 |
| Understanding Actors and Evaluating Personae with Gaussian Embeddings |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Understanding Dropouts in MOOCs |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Understanding Learned Models by Identifying Important Features at the Right Resolution |
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❌ |
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❌ |
❌ |
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4 |
| Understanding Persuasion Cascades in Online Product Rating Systems |
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❌ |
❌ |
❌ |
❌ |
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0 |
| Understanding Pictograph with Facial Features: End-to-End Sentence-Level Lip Reading of Chinese |
❌ |
❌ |
❌ |
✅ |
✅ |
❌ |
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3 |
| Understanding VAEs in Fisher-Shannon Plane |
❌ |
❌ |
✅ |
✅ |
❌ |
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3 |
| Unified Embedding Alignment with Missing Views Inferring for Incomplete Multi-View Clustering |
✅ |
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✅ |
✅ |
❌ |
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4 |
| Universal Approximation Property and Equivalence of Stochastic Computing-Based Neural Networks and Binary Neural Networks |
❌ |
❌ |
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❌ |
❌ |
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0 |
| Unknown Agents in Friends Oriented Hedonic Games: Stability and Complexity |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Unseen Word Representation by Aligning Heterogeneous Lexical Semantic Spaces |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
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3 |
| Unsupervised Bilingual Lexicon Induction from Mono-Lingual Multimodal Data |
✅ |
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3 |
| Unsupervised Controllable Text Formalization |
❌ |
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4 |
| Unsupervised Cross-Spectral Stereo Matching by Learning to Synthesize |
❌ |
❌ |
✅ |
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3 |
| Unsupervised Domain Adaptation Based on Source-Guided Discrepancy |
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4 |
| Unsupervised Domain Adaptation by Matching Distributions Based on the Maximum Mean Discrepancy via Unilateral Transformations |
❌ |
❌ |
✅ |
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2 |
| Unsupervised Fake News Detection on Social Media: A Generative Approach |
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3 |
| Unsupervised Feature Selection by Pareto Optimization |
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3 |
| Unsupervised Learning Helps Supervised Neural Word Segmentation |
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4 |
| Unsupervised Learning with Contrastive Latent Variable Models |
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3 |
| Unsupervised Meta-Learning of Figure-Ground Segmentation via Imitating Visual Effects |
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✅ |
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❌ |
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3 |
| Unsupervised Neural Machine Translation with SMT as Posterior Regularization |
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❌ |
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❌ |
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3 |
| Unsupervised Post-Processing of Word Vectors via Conceptor Negation |
✅ |
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✅ |
❌ |
❌ |
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4 |
| Unsupervised Stylish Image Description Generation via Domain Layer Norm |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| Unsupervised Transfer Learning for Spoken Language Understanding in Intelligent Agents |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Updates in Human-AI Teams: Understanding and Addressing the Performance/Compatibility Tradeoff |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Using Benson’s Algorithm for Regularization Parameter Tracking |
✅ |
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✅ |
❌ |
❌ |
✅ |
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4 |
| Utilizing Class Information for Deep Network Representation Shaping |
❌ |
✅ |
✅ |
✅ |
❌ |
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✅ |
4 |
| Validation of Growing Knowledge Graphs by Abductive Text Evidences |
✅ |
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❌ |
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4 |
| Variance Reduction in Monte Carlo Counterfactual Regret Minimization (VR-MCCFR) for Extensive Form Games Using Baselines |
✅ |
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✅ |
❌ |
❌ |
❌ |
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3 |
| Variational Autoencoder with Implicit Optimal Priors |
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✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Verification of RNN-Based Neural Agent-Environment Systems |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
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6 |
| Verifying Robustness of Gradient Boosted Models |
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❌ |
✅ |
❌ |
✅ |
✅ |
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4 |
| Very Hard Electoral Control Problems |
✅ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
6 |
| Video Imprint Segmentation for Temporal Action Detection in Untrimmed Videos |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
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4 |
| Video Inpainting by Jointly Learning Temporal Structure and Spatial Details |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
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4 |
| Video Object Detection with Locally-Weighted Deformable Neighbors |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| VidyutVanika: A Reinforcement Learning Based Broker Agent for a Power Trading Competition |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| View Inter-Prediction GAN: Unsupervised Representation Learning for 3D Shapes by Learning Global Shape Memories to Support Local View Predictions |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
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3 |
| Violence Rating Prediction from Movie Scripts |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Virtual-Taobao: Virtualizing Real-World Online Retail Environment for Reinforcement Learning |
✅ |
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❌ |
❌ |
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❌ |
✅ |
2 |
| VistaNet: Visual Aspect Attention Network for Multimodal Sentiment Analysis |
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✅ |
❌ |
✅ |
❌ |
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3 |
| Visual Place Recognition via Robust ℓ2-Norm Distance Based Holism and Landmark Integration |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Visual-Semantic Graph Reasoning for Pedestrian Attribute Recognition |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Walrasian Dynamics in Multi-Unit Markets |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Weakly Supervised Scene Parsing with Point-Based Distance Metric Learning |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
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5 |
| Weakly-Supervised Hierarchical Text Classification |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Weakly-Supervised Simultaneous Evidence Identification and Segmentation for Automated Glaucoma Diagnosis |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Weighted Abstract Dialectical Frameworks through the Lens of Approximation Fixpoint Theory |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Weighted Channel Dropout for Regularization of Deep Convolutional Neural Network |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Weighted Oblique Decision Trees |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Weisfeiler and Leman Go Neural: Higher-Order Graph Neural Networks |
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✅ |
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❌ |
❌ |
✅ |
4 |
| What Is One Grain of Sand in the Desert? Analyzing Individual Neurons in Deep NLP Models |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| What Should I Learn First: Introducing LectureBank for NLP Education and Prerequisite Chain Learning |
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❌ |
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3 |
| What and Where the Themes Dominate in Image |
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✅ |
✅ |
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✅ |
3 |
| What if We Simply Swap the Two Text Fragments? A Straightforward yet Effective Way to Test the Robustness of Methods to Confounding Signals in Nature Language Inference Tasks |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
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3 |
| When Do Envy-Free Allocations Exist? |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| When Do Words Matter? Understanding the Impact of Lexical Choice on Audience Perception Using Individual Treatment Effect Estimation |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Where to Go Next: A Spatio-Temporal Gated Network for Next POI Recommendation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Which Factorization Machine Modeling Is Better: A Theoretical Answer with Optimal Guarantee |
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❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| Who Blames Whom in a Crisis? Detecting Blame Ties from News Articles Using Neural Networks |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| Word Embedding as Maximum A Posteriori Estimation |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
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5 |
| Words Can Shift: Dynamically Adjusting Word Representations Using Nonverbal Behaviors |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| X-DMM: Fast and Scalable Model Based Text Clustering |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
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4 |
| Y2Seq2Seq: Cross-Modal Representation Learning for 3D Shape and Text by Joint Reconstruction and Prediction of View and Word Sequences |
❌ |
❌ |
✅ |
✅ |
❌ |
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3 |
| You Get What You Share: Incentives for a Sharing Economy |
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❌ |
❌ |
✅ |
1 |
| Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference |
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✅ |
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❌ |
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❌ |
❌ |
1 |
| Zero-Shot Adaptive Transfer for Conversational Language Understanding |
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❌ |
❌ |
✅ |
❌ |
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✅ |
2 |
| Zero-Shot Neural Transfer for Cross-Lingual Entity Linking |
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✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Zero-Shot Object Detection with Textual Descriptions |
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✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| f-Similarity Preservation Loss for Soft Labels: A Demonstration on Cross-Corpus Speech Emotion Recognition |
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✅ |
✅ |
❌ |
✅ |
✅ |
4 |
| “Bilingual Expert” Can Find Translation Errors |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| “Reverse Gerrymandering”: Manipulation in Multi-Group Decision Making |
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❌ |
❌ |
❌ |
❌ |
✅ |
1 |