| 3DViewGraph: Learning Global Features for 3D Shapes from A Graph of Unordered Views with Attention |
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3 |
| A Comparative Study of Distributional and Symbolic Paradigms for Relational Learning |
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3 |
| A Contribution to the Critique of Liquid Democracy |
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0 |
| A Convergence Analysis of Distributed SGD with Communication-Efficient Gradient Sparsification |
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3 |
| A Decomposition Approach for Urban Anomaly Detection Across Spatiotemporal Data |
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2 |
| A Deep Bi-directional Attention Network for Human Motion Recovery |
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4 |
| A Deep Generative Model for Code Switched Text |
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3 |
| A Degeneracy Framework for Scalable Graph Autoencoders |
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5 |
| A Document-grounded Matching Network for Response Selection in Retrieval-based Chatbots |
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3 |
| A Dual Reinforcement Learning Framework for Unsupervised Text Style Transfer |
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5 |
| A Goal-Driven Tree-Structured Neural Model for Math Word Problems |
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4 |
| A Gradient-Based Split Criterion for Highly Accurate and Transparent Model Trees |
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4 |
| A Latent Variable Model for Learning Distributional Relation Vectors |
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5 |
| A Modal Characterization Theorem for a Probabilistic Fuzzy Description Logic |
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0 |
| A Novel Distribution-Embedded Neural Network for Sensor-Based Activity Recognition |
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5 |
| A Parameterized Perspective on Protecting Elections |
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1 |
| A Part Power Set Model for Scale-Free Person Retrieval |
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5 |
| A Practical Semi-Parametric Contextual Bandit |
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2 |
| A Principled Approach for Learning Task Similarity in Multitask Learning |
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2 |
| A Privacy Preserving Collusion Secure DCOP Algorithm |
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5 |
| A Probabilistic Logic for Resource-Bounded Multi-Agent Systems |
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0 |
| A Quantitative Analysis of Multi-Winner Rules |
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2 |
| A Quantum-inspired Classical Algorithm for Separable Non-negative Matrix Factorization |
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1 |
| A Regularized Opponent Model with Maximum Entropy Objective |
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2 |
| A Restart-based Rank-1 Evolution Strategy for Reinforcement Learning |
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3 |
| A Review-Driven Neural Model for Sequential Recommendation |
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2 |
| A Semantics-based Model for Predicting Children's Vocabulary |
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2 |
| A Span-based Joint Model for Opinion Target Extraction and Target Sentiment Classification |
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3 |
| A Strongly Asymptotically Optimal Agent in General Environments |
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4 |
| A Tractable, Expressive, and Eventually Complete First-Order Logic of Limited Belief |
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0 |
| A Value-based Trust Assessment Model for Multi-agent Systems |
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0 |
| A Vectorized Relational Graph Convolutional Network for Multi-Relational Network Alignment |
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2 |
| A*+IDA*: A Simple Hybrid Search Algorithm |
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3 |
| AI-powered Posture Training: Application of Machine Learning in Sitting Posture Recognition Using the LifeChair Smart Cushion |
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0 |
| ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs |
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1 |
| ARMIN: Towards a More Efficient and Light-weight Recurrent Memory Network |
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4 |
| ASP-based Discovery of Semi-Markovian Causal Models under Weaker Assumptions |
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2 |
| ATSIS: Achieving the Ad hoc Teamwork by Sub-task Inference and Selection |
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1 |
| ATTAIN: Attention-based Time-Aware LSTM Networks for Disease Progression Modeling |
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2 |
| Accelerated Incremental Gradient Descent using Momentum Acceleration with Scaling Factor |
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3 |
| Accelerated Inference Framework of Sparse Neural Network Based on Nested Bitmask Structure |
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2 |
| Accelerating Extreme Classification via Adaptive Feature Agglomeration |
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5 |
| Achieving Causal Fairness through Generative Adversarial Networks |
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2 |
| Achieving a Fairer Future by Changing the Past |
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1 |
| Acquiring Integer Programs from Data |
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5 |
| Action Space Learning for Heterogeneous User Behavior Prediction |
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4 |
| Active Learning within Constrained Environments through Imitation of an Expert Questioner |
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3 |
| ActiveHNE: Active Heterogeneous Network Embedding |
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4 |
| Ad Hoc Teamwork With Behavior Switching Agents |
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2 |
| AdaLinUCB: Opportunistic Learning for Contextual Bandits |
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4 |
| Adapting BERT for Target-Oriented Multimodal Sentiment Classification |
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4 |
| Adaptive Ensemble Active Learning for Drifting Data Stream Mining |
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3 |
| Adaptive Thompson Sampling Stacks for Memory Bounded Open-Loop Planning |
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4 |
| Adaptive User Modeling with Long and Short-Term Preferences for Personalized Recommendation |
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4 |
| AddGraph: Anomaly Detection in Dynamic Graph Using Attention-based Temporal GCN |
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3 |
| Advantage Amplification in Slowly Evolving Latent-State Environments |
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1 |
| Adversarial Examples for Graph Data: Deep Insights into Attack and Defense |
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3 |
| Adversarial Graph Embedding for Ensemble Clustering |
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3 |
| Adversarial Imitation Learning from Incomplete Demonstrations |
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3 |
| Adversarial Incomplete Multi-view Clustering |
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2 |
| Adversarial Transfer for Named Entity Boundary Detection with Pointer Networks |
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4 |
| Advocacy Learning: Learning through Competition and Class-Conditional Representations |
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5 |
| Affine Equivariant Autoencoder |
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3 |
| Aggregating Incomplete Pairwise Preferences by Weight |
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0 |
| Aggressive Driving Saves More Time? Multi-task Learning for Customized Travel Time Estimation |
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2 |
| Aligning Learning Outcomes to Learning Resources: A Lexico-Semantic Spatial Approach |
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1 |
| Almost Envy-Freeness in Group Resource Allocation |
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0 |
| Amalgamating Filtered Knowledge: Learning Task-customized Student from Multi-task Teachers |
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5 |
| AmazonQA: A Review-Based Question Answering Task |
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3 |
| An ASP Approach to Generate Minimal Countermodels in Intuitionistic Propositional Logic |
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4 |
| An Actor-Critic-Attention Mechanism for Deep Reinforcement Learning in Multi-view Environments |
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2 |
| An Asymptotically Optimal VCG Redistribution Mechanism for the Public Project Problem |
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0 |
| An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents |
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2 |
| An Efficient Algorithm for Skeptical Preferred Acceptance in Dynamic Argumentation Frameworks |
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3 |
| An Efficient Evolutionary Algorithm for Minimum Cost Submodular Cover |
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4 |
| An End-to-End Community Detection Model: Integrating LDA into Markov Random Field via Factor Graph |
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2 |
| An Evolution Strategy with Progressive Episode Lengths for Playing Games |
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4 |
| An Experimental View on Committees Providing Justified Representation |
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2 |
| An Input-aware Factorization Machine for Sparse Prediction |
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4 |
| An Ordinal Banzhaf Index for Social Ranking |
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0 |
| Answer Set Programming for Judgment Aggregation |
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3 |
| Answering Binary Causal Questions Through Large-Scale Text Mining: An Evaluation Using Cause-Effect Pairs from Human Experts |
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1 |
| Anytime Bottom-Up Rule Learning for Knowledge Graph Completion |
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5 |
| Anytime Heuristic for Weighted Matching Through Altruism-Inspired Behavior |
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3 |
| Approval-Based Elections and Distortion of Voting Rules |
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0 |
| Approximability of Constant-horizon Constrained POMDP |
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1 |
| Approximate Manifold Regularization: Scalable Algorithm and Generalization Analysis |
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3 |
| Approximate Optimal Transport for Continuous Densities with Copulas |
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4 |
| Approximately Maximizing the Broker's Profit in a Two-sided Market |
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1 |
| Approximating Integer Solution Counting via Space Quantification for Linear Constraints |
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5 |
| Aspect-Based Sentiment Classification with Attentive Neural Turing Machines |
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2 |
| Assumed Density Filtering Q-learning |
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4 |
| AsymDPOP: Complete Inference for Asymmetric Distributed Constraint Optimization Problems |
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1 |
| Asynchronous Stochastic Frank-Wolfe Algorithms for Non-Convex Optimization |
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4 |
| Athanor: High-Level Local Search Over Abstract Constraint Specifications in Essence |
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5 |
| AttnSense: Multi-level Attention Mechanism For Multimodal Human Activity Recognition |
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4 |
| Attribute Aware Pooling for Pedestrian Attribute Recognition |
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5 |
| Attribute-Aware Convolutional Neural Networks for Facial Beauty Prediction |
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5 |
| Attributed Graph Clustering via Adaptive Graph Convolution |
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4 |
| Attributed Graph Clustering: A Deep Attentional Embedding Approach |
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3 |
| Attributed Subspace Clustering |
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3 |
| AugBoost: Gradient Boosting Enhanced with Step-Wise Feature Augmentation |
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5 |
| Augmenting Transfer Learning with Semantic Reasoning |
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3 |
| Automated Machine Learning with Monte-Carlo Tree Search |
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6 |
| Automated Negotiation with Gaussian Process-based Utility Models |
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2 |
| Automatic Grassland Degradation Estimation Using Deep Learning |
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3 |
| Automatic Successive Reinforcement Learning with Multiple Auxiliary Rewards |
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3 |
| Automatic Verification of FSA Strategies via Counterexample-Guided Local Search for Invariants |
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3 |
| Autoregressive Policies for Continuous Control Deep Reinforcement Learning |
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2 |
| Average-case Analysis of the Assignment Problem with Independent Preferences |
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0 |
| BAYHENN: Combining Bayesian Deep Learning and Homomorphic Encryption for Secure DNN Inference |
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✅ |
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5 |
| BN-invariant Sharpness Regularizes the Training Model to Better Generalization |
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4 |
| BPAM: Recommendation Based on BP Neural Network with Attention Mechanism |
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3 |
| Balanced Clustering: A Uniform Model and Fast Algorithm |
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5 |
| Balanced Ranking with Diversity Constraints |
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1 |
| Balancing Explicability and Explanations in Human-Aware Planning |
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3 |
| Bayesian Inference of Linear Temporal Logic Specifications for Contrastive Explanations |
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4 |
| Bayesian Parameter Estimation for Nonlinear Dynamics Using Sensitivity Analysis |
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1 |
| Bayesian Uncertainty Matching for Unsupervised Domain Adaptation |
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2 |
| Be a Leader or Become a Follower: The Strategy to Commit to with Multiple Leaders |
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0 |
| BeatGAN: Anomalous Rhythm Detection using Adversarially Generated Time Series |
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6 |
| Belief Propagation Network for Hard Inductive Semi-Supervised Learning |
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5 |
| Belief Revision Operators with Varying Attitudes Towards Initial Beliefs |
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0 |
| Belief Update without Compactness in Non-finitary Languages |
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0 |
| Best Answers over Incomplete Data : Complexity and First-Order Rewritings |
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0 |
| Beyond Product Quantization: Deep Progressive Quantization for Image Retrieval |
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4 |
| Beyond Word Attention: Using Segment Attention in Neural Relation Extraction |
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✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| BiOWA for Preference Aggregation with Bipolar Scales: Application to Fair Optimization in Combinatorial Domains |
❌ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
3 |
| Bidirectional Active Learning with Gold-Instance-Based Human Training |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Binarized Collaborative Filtering with Distilling Graph Convolutional Network |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Binarized Neural Networks for Resource-Efficient Hashing with Minimizing Quantization Loss |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Boosting Causal Embeddings via Potential Verb-Mediated Causal Patterns |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Boosting for Comparison-Based Learning |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Boundary Perception Guidance: A Scribble-Supervised Semantic Segmentation Approach |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Branch-and-Cut-and-Price for Multi-Agent Pathfinding |
❌ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
4 |
| Building Personalized Simulator for Interactive Search |
✅ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| CFM: Convolutional Factorization Machines for Context-Aware Recommendation |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| CLVSA: A Convolutional LSTM Based Variational Sequence-to-Sequence Model with Attention for Predicting Trends of Financial Markets |
❌ |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
3 |
| CNN-Based Chinese NER with Lexicon Rethinking |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| COP: Customized Deep Model Compression via Regularized Correlation-Based Filter-Level Pruning |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Cap-and-Trade Emissions Regulation: A Strategic Analysis |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Capturing Spatial and Temporal Patterns for Facial Landmark Tracking through Adversarial Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Cascaded Algorithm-Selection and Hyper-Parameter Optimization with Extreme-Region Upper Confidence Bound Bandit |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Cascading Non-Stationary Bandits: Online Learning to Rank in the Non-Stationary Cascade Model |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Causal Discovery with Cascade Nonlinear Additive Noise Model |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
3 |
| CensNet: Convolution with Edge-Node Switching in Graph Neural Networks |
✅ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
6 |
| Chasing Sets: How to Use Existential Rules for Expressive Reasoning |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
2 |
| Civic Crowdfunding for Agents with Negative Valuations and Agents with Asymmetric Beliefs |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Classification with Label Distribution Learning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Closed-Loop Memory GAN for Continual Learning |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
3 |
| Co-Attentive Multi-Task Learning for Explainable Recommendation |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| CoSegNet: Image Co-segmentation using a Conditional Siamese Convolutional Network |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Coarse-to-Fine Image Inpainting via Region-wise Convolutions and Non-Local Correlation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Cold-Start Aware Deep Memory Network for Multi-Entity Aspect-Based Sentiment Analysis |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Collaborative Metric Learning with Memory Network for Multi-Relational Recommender Systems |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Color-Sensitive Person Re-Identification |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Combining ADMM and the Augmented Lagrangian Method for Efficiently Handling Many Constraints |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Commit Message Generation for Source Code Changes |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Community Detection and Link Prediction via Cluster-driven Low-rank Matrix Completion |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Compact Representation of Value Function in Partially Observable Stochastic Games |
✅ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
4 |
| Comparing Options with Argument Schemes Powered by Cancellation |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Compilation of Logical Arguments |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
3 |
| Complexity of Manipulating and Controlling Approval-Based Multiwinner Voting |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Comprehensive Semi-Supervised Multi-Modal Learning |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Computational Aspects of Equilibria in Discrete Preference Games |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Conditional GAN with Discriminative Filter Generation for Text-to-Video Synthesis |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Conditions for Avoiding Node Re-expansions in Bounded Suboptimal Search |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Conditions on Features for Temporal Difference-Like Methods to Converge |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Confirmatory Bayesian Online Change Point Detection in the Covariance Structure of Gaussian Processes |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Connectionist Temporal Modeling of Video and Language: a Joint Model for Translation and Sign Labeling |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Constraint Programming for Mining Borders of Frequent Itemsets |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Constraint-Based Scheduling with Complex Setup Operations: An Iterative Two-Layer Approach |
✅ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
4 |
| Controllable Neural Story Plot Generation via Reward Shaping |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Converging on Common Knowledge |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Convolutional Auto-encoding of Sentence Topics for Image Paragraph Generation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Convolutional Gaussian Embeddings for Personalized Recommendation with Uncertainty |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Cooperative Pruning in Cross-Domain Deep Neural Network Compression |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Coreference Aware Representation Learning for Neural Named Entity Recognition |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Correct-and-Memorize: Learning to Translate from Interactive Revisions |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Correlating Preferences and Attributes: Nearly Single-Crossing Profiles |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Correlation-Sensitive Next-Basket Recommendation |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| CounterFactual Regression with Importance Sampling Weights |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Counterexample-Guided Strategy Improvement for POMDPs Using Recurrent Neural Networks |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Counterfactual Fairness: Unidentification, Bound and Algorithm |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Crafting Efficient Neural Graph of Large Entropy |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Cross-City Transfer Learning for Deep Spatio-Temporal Prediction |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Curriculum Learning for Cumulative Return Maximization |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
3 |
| Cutset Bayesian Networks: A New Representation for Learning Rao-Blackwellised Graphical Models |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| DANE: Domain Adaptive Network Embedding |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| DARec: Deep Domain Adaptation for Cross-Domain Recommendation via Transferring Rating Patterns |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| DBDNet: Learning Bi-directional Dynamics for Early Action Prediction |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| DDL: Deep Dictionary Learning for Predictive Phenotyping |
✅ |
✅ |
✅ |
✅ |
✅ |
✅ |
✅ |
7 |
| DMRAN:A Hierarchical Fine-Grained Attention-Based Network for Recommendation |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| DSRN: A Deep Scale Relationship Network for Scene Text Detection |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Data Complexity and Rewritability of Ontology-Mediated Queries in Metric Temporal Logic under the Event-Based Semantics |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Data Poisoning Attack against Knowledge Graph Embedding |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Data Poisoning against Differentially-Private Learners: Attacks and Defenses |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| DatalogMTL: Computational Complexity and Expressive Power |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Daytime Sleepiness Level Prediction Using Respiratory Information |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Deanonymizing Social Networks Using Structural Information |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Decentralized Optimization with Edge Sampling |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Decidability of Model Checking Multi-Agent Systems with Regular Expressions against Epistemic HS Specifications |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Decision Making for Improving Maritime Traffic Safety Using Constraint Programming |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Decoding EEG by Visual-guided Deep Neural Networks |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Deep Active Learning for Anchor User Prediction |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Deep Active Learning with Adaptive Acquisition |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Deep Adversarial Multi-view Clustering Network |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Deep Adversarial Social Recommendation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| Deep Cascade Generation on Point Sets |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Deep Correlated Predictive Subspace Learning for Incomplete Multi-View Semi-Supervised Classification |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Deep Light-field-driven Saliency Detection from a Single View |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Deep Mask Memory Network with Semantic Dependency and Context Moment for Aspect Level Sentiment Classification |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
2 |
| Deep Multi-Task Learning with Adversarial-and-Cooperative Nets |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Deep Recurrent Quantization for Generating Sequential Binary Codes |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Deep Session Interest Network for Click-Through Rate Prediction |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Deep Spectral Kernel Learning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| DeepAPF: Deep Attentive Probabilistic Factorization for Multi-site Video Recommendation |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| DeepCU: Integrating both Common and Unique Latent Information for Multimodal Sentiment Analysis |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| DeepFlow: Detecting Optimal User Experience From Physiological Data Using Deep Neural Networks |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| DeepInspect: A Black-box Trojan Detection and Mitigation Framework for Deep Neural Networks |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| DeepMellow: Removing the Need for a Target Network in Deep Q-Learning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active Learning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Deeply-learned Hybrid Representations for Facial Age Estimation |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Deliberation Learning for Image-to-Image Translation |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| DeltaDou: Expert-level Doudizhu AI through Self-play |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Demystifying the Combination of Dynamic Slicing and Spectrum-based Fault Localization |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Dense Temporal Convolution Network for Sign Language Translation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Dense Transformer Networks for Brain Electron Microscopy Image Segmentation |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Densely Connected Attention Flow for Visual Question Answering |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Densely Supervised Hierarchical Policy-Value Network for Image Paragraph Generation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Depth-First Memory-Limited AND/OR Search and Unsolvability in Cyclic Search Spaces |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Detecting Robust Co-Saliency with Recurrent Co-Attention Neural Network |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Deterministic Routing between Layout Abstractions for Multi-Scale Classification of Visually Rich Documents |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| DiffChaser: Detecting Disagreements for Deep Neural Networks |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Differentially Private Iterative Gradient Hard Thresholding for Sparse Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Differentially Private Optimal Transport: Application to Domain Adaptation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Difficulty Controllable Generation of Reading Comprehension Questions |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Diffusion and Auction on Graphs |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Dilated Convolution with Dilated GRU for Music Source Separation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Direction-Optimizing Breadth-First Search with External Memory Storage |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Discovering Regularities from Traditional Chinese Medicine Prescriptions via Bipartite Embedding Model |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Discrete Binary Coding based Label Distribution Learning |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Discrete Trust-aware Matrix Factorization for Fast Recommendation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Discriminative Sample Generation for Deep Imbalanced Learning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Discriminative and Correlative Partial Multi-Label Learning |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Disparity-preserved Deep Cross-platform Association for Cross-platform Video Recommendation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Dispatching Through Pricing: Modeling Ride-Sharing and Designing Dynamic Prices |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Distributed Collaborative Feature Selection Based on Intermediate Representation |
✅ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
6 |
| Diversity-Inducing Policy Gradient: Using Maximum Mean Discrepancy to Find a Set of Diverse Policies |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Do You Need Infinite Time? |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| DoubleLex Revisited and Beyond |
❌ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
3 |
| Dual Self-Paced Graph Convolutional Network: Towards Reducing Attribute Distortions Induced by Topology |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Dual Visual Attention Network for Visual Dialog |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Dual-Path in Dual-Path Network for Single Image Dehazing |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Dual-View Variational Autoencoders for Semi-Supervised Text Matching |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| DyAt Nets: Dynamic Attention Networks for State Forecasting in Cyber-Physical Systems |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Dynamic Electronic Toll Collection via Multi-Agent Deep Reinforcement Learning with Edge-Based Graph Convolutional Networks |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Dynamic Feature Fusion for Semantic Edge Detection |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Dynamic Hypergraph Neural Networks |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Dynamic Item Block and Prediction Enhancing Block for Sequential Recommendation |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Dynamic logic of parallel propositional assignments and its applications to planning |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Dynamically Route Hierarchical Structure Representation to Attentive Capsule for Text Classification |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Dynamically Visual Disambiguation of Keyword-based Image Search |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| EL Embeddings: Geometric Construction of Models for the Description Logic EL++ |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Earlier Attention? Aspect-Aware LSTM for Aspect-Based Sentiment Analysis |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Earliest-Completion Scheduling of Contract Algorithms with End Guarantees |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Early Discovery of Emerging Entities in Microblogs |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
4 |
| Efficient Non-parametric Bayesian Hawkes Processes |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Efficient Protocol for Collaborative Dictionary Learning in Decentralized Networks |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Efficient Regularization Parameter Selection for Latent Variable Graphical Models via Bi-Level Optimization |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Election with Bribe-Effect Uncertainty: A Dichotomy Result |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| End-to-End Multi-Perspective Matching for Entity Resolution |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Energy-Efficient Slithering Gait Exploration for a Snake-Like Robot Based on Reinforcement Learning |
❌ |
✅ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Enhancing Stock Movement Prediction with Adversarial Training |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Enriching Ontology-based Data Access with Provenance |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
❌ |
4 |
| Ensemble-based Ultrahigh-dimensional Variable Screening |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| Entangled Kernels |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Entropy-Penalized Semidefinite Programming |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Enumerating Potential Maximal Cliques via SAT and ASP |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
6 |
| Equally-Guided Discriminative Hashing for Cross-modal Retrieval |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Equilibrium Characterization for Data Acquisition Games |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Equitable Allocations of Indivisible Goods |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Estimating Causal Effects of Tone in Online Debates |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Evaluating the Interpretability of the Knowledge Compilation Map: Communicating Logical Statements Effectively |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Exact Bernoulli Scan Statistics using Binary Decision Diagrams |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Exchangeability and Kernel Invariance in Trained MLPs |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Experience Replay Optimization |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Explainable Fashion Recommendation: A Semantic Attribute Region Guided Approach |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Explaining Reinforcement Learning to Mere Mortals: An Empirical Study |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Explanations for Query Answers under Existential Rules |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Explicitly Coordinated Policy Iteration |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Exploiting Interaction Links for Node Classification with Deep Graph Neural Networks |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Exploiting Persona Information for Diverse Generation of Conversational Responses |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Exploiting Social Influence to Control Elections Based on Scoring Rules |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Exploiting the Sign of the Advantage Function to Learn Deterministic Policies in Continuous Domains |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Explore Truthful Incentives for Tasks with Heterogenous Levels of Difficulty in the Sharing Economy |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Exploring Computational User Models for Agent Policy Summarization |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Exploring and Distilling Cross-Modal Information for Image Captioning |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Exploring the Task Cooperation in Multi-goal Visual Navigation |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Extensible Cross-Modal Hashing |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Extracting Entities and Events as a Single Task Using a Transition-Based Neural Model |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Extrapolating Paths with Graph Neural Networks |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| E²GAN: End-to-End Generative Adversarial Network for Multivariate Time Series Imputation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| FABA: An Algorithm for Fast Aggregation against Byzantine Attacks in Distributed Neural Networks |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| FAHT: An Adaptive Fairness-aware Decision Tree Classifier |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| FSM: A Fast Similarity Measurement for Gene Regulatory Networks via Genes' Influence Power |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| FaRM: Fair Reward Mechanism for Information Aggregation in Spontaneous Localized Settings |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Face Photo-Sketch Synthesis via Knowledge Transfer |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Failure-Scenario Maker for Rule-Based Agent using Multi-agent Adversarial Reinforcement Learning and its Application to Autonomous Driving |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Fair Allocation of Indivisible Goods and Chores |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Fair Online Allocation of Perishable Goods and its Application to Electric Vehicle Charging |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Fairness Towards Groups of Agents in the Allocation of Indivisible Items |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Fairwalk: Towards Fair Graph Embedding |
✅ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| FakeTables: Using GANs to Generate Functional Dependency Preserving Tables with Bounded Real Data |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
✅ |
3 |
| Fast Algorithm for K-Truss Discovery on Public-Private Graphs |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Fast and Accurate Classification with a Multi-Spike Learning Algorithm for Spiking Neurons |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Fast and Robust Multi-View Multi-Task Learning via Group Sparsity |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Faster Distributed Deep Net Training: Computation and Communication Decoupled Stochastic Gradient Descent |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
6 |
| Faster Dynamic Controllability Checking in Temporal Networks with Integer Bounds |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Feature Evolution Based Multi-Task Learning for Collaborative Filtering with Social Trust |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Feature Prioritization and Regularization Improve Standard Accuracy and Adversarial Robustness |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Feature-level Deeper Self-Attention Network for Sequential Recommendation |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Finding Optimal Solutions in HTN Planning - A SAT-based Approach |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
6 |
| Finding Statistically Significant Interactions between Continuous Features |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Fine-grained Event Categorization with Heterogeneous Graph Convolutional Networks |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
4 |
| FireCast: Leveraging Deep Learning to Predict Wildfire Spread |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Flexible Multi-View Representation Learning for Subspace Clustering |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Flexible Representative Democracy: An Introduction with Binary Issues |
❌ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
3 |
| From Statistical Transportability to Estimating the Effect of Stochastic Interventions |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| From Words to Sentences: A Progressive Learning Approach for Zero-resource Machine Translation with Visual Pivots |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Fully Distributed Bayesian Optimization with Stochastic Policies |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| GAN-EM: GAN Based EM Learning Framework |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| GANAK: A Scalable Probabilistic Exact Model Counter |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| GANs for Semi-Supervised Opinion Spam Detection |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| GCN-LASE: Towards Adequately Incorporating Link Attributes in Graph Convolutional Networks |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| GSN: A Graph-Structured Network for Multi-Party Dialogues |
✅ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
6 |
| GSTNet: Global Spatial-Temporal Network for Traffic Flow Prediction |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Generalized Majorization-Minimization for Non-Convex Optimization |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Generalized Potential Heuristics for Classical Planning |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Generalized Zero-Shot Vehicle Detection in Remote Sensing Imagery via Coarse-to-Fine Framework |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Generating Multiple Diverse Responses with Multi-Mapping and Posterior Mapping Selection |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Generative Image Inpainting with Submanifold Alignment |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Generative Visual Dialogue System via Weighted Likelihood Estimation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Geo-ALM: POI Recommendation by Fusing Geographical Information and Adversarial Learning Mechanism |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Geometric Understanding for Unsupervised Subspace Learning |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
❌ |
4 |
| Getting in Shape: Word Embedding SubSpaces |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the Hamming Distance |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
❌ |
4 |
| Governance by Glass-Box: Implementing Transparent Moral Bounds for AI Behaviour |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Gradient Boosting with Piece-Wise Linear Regression Trees |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Graph Contextualized Self-Attention Network for Session-based Recommendation |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Graph Convolutional Network Hashing for Cross-Modal Retrieval |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Graph Convolutional Networks on User Mobility Heterogeneous Graphs for Social Relationship Inference |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Graph Convolutional Networks using Heat Kernel for Semi-supervised Learning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Graph Mining Meets Crowdsourcing: Extracting Experts for Answer Aggregation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Graph Space Embedding |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Graph WaveNet for Deep Spatial-Temporal Graph Modeling |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Graph and Autoencoder Based Feature Extraction for Zero-shot Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Graph-based Neural Sentence Ordering |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Graphical One-Sided Markets |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Group LASSO with Asymmetric Structure Estimation for Multi-Task Learning |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Group Reconstruction and Max-Pooling Residual Capsule Network |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Group-Fairness in Influence Maximization |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
3 |
| Group-based Learning of Disentangled Representations with Generalizability for Novel Contents |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Guarantees for Sound Abstractions for Generalized Planning |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| HDI-Forest: Highest Density Interval Regression Forest |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| HMLasso: Lasso with High Missing Rate |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Hallucinating Optical Flow Features for Video Classification |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Harnessing the Vulnerability of Latent Layers in Adversarially Trained Models |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Heavy-ball Algorithms Always Escape Saddle Points |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Heterogeneous Graph Matching Networks for Unknown Malware Detection |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Heuristic Search for Homology Localization Problem and Its Application in Cardiac Trabeculae Reconstruction |
❌ |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
1 |
| Hi-Fi Ark: Deep User Representation via High-Fidelity Archive Network |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
3 |
| Hierarchical Diffusion Attention Network |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Hierarchical Inter-Attention Network for Document Classification with Multi-Task Learning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Hierarchical Representation Learning for Bipartite Graphs |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| High Dimensional Bayesian Optimization via Supervised Dimension Reduction |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| High Performance Gesture Recognition via Effective and Efficient Temporal Modeling |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Hill Climbing on Value Estimates for Search-control in Dyna |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| HorNet: A Hierarchical Offshoot Recurrent Network for Improving Person Re-ID via Image Captioning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| How Hard Is the Manipulative Design of Scoring Systems? |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| How Well Do Machines Perform on IQ tests: a Comparison Study on a Large-Scale Dataset |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| How to Handle Missing Values in Multi-Criteria Decision Aiding? |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| How to Tame Your Anticipatory Algorithm |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
✅ |
5 |
| Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Hybrid Actor-Critic Reinforcement Learning in Parameterized Action Space |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Hybrid Item-Item Recommendation via Semi-Parametric Embedding |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Hyper-parameter Tuning under a Budget Constraint |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Hypergraph Induced Convolutional Manifold Networks |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| IRC-GAN: Introspective Recurrent Convolutional GAN for Text-to-video Generation |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| ISLF: Interest Shift and Latent Factors Combination Model for Session-based Recommendation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Identifying vulnerabilities in trust and reputation systems |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Image Captioning with Compositional Neural Module Networks |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Image-to-Image Translation with Multi-Path Consistency Regularization |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Imitation Learning from Video by Leveraging Proprioception |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Imitative Attacker Deception in Stackelberg Security Games |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Improved Algorithm on Online Clustering of Bandits |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Improved Heuristics for Multi-Agent Path Finding with Conflict-Based Search |
❌ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
2 |
| Improving Cross-Domain Performance for Relation Extraction via Dependency Prediction and Information Flow Control |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Improving Cross-lingual Entity Alignment via Optimal Transport |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Improving Customer Satisfaction in Bike Sharing Systems through Dynamic Repositioning |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Improving Law Enforcement Daily Deployment Through Machine Learning-Informed Optimization under Uncertainty |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Improving Multilingual Sentence Embedding using Bi-directional Dual Encoder with Additive Margin Softmax |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Improving Nash Social Welfare Approximations |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Improving representation learning in autoencoders via multidimensional interpolation and dual regularizations |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Incorporating Structural Information for Better Coreference Resolution |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
4 |
| Incremental Elicitation of Rank-Dependent Aggregation Functions based on Bayesian Linear Regression |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Incremental Few-Shot Learning for Pedestrian Attribute Recognition |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Incremental Learning of Planning Actions in Model-Based Reinforcement Learning |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Indirect Trust is Simple to Establish |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Inferring Substitutable Products with Deep Network Embedding |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Influence of State-Variable Constraints on Partially Observable Monte Carlo Planning |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Integrating Decision Sharing with Prediction in Decentralized Planning for Multi-Agent Coordination under Uncertainty |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Integrating Pseudo-Boolean Constraint Reasoning in Multi-Objective Evolutionary Algorithms |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Inter-node Hellinger Distance based Decision Tree |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| InteractionNN: A Neural Network for Learning Hidden Features in Sparse Prediction |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Interactive Reinforcement Learning with Dynamic Reuse of Prior Knowledge from Human and Agent Demonstrations |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Interactive Teaching Algorithms for Inverse Reinforcement Learning |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Interpolation Consistency Training for Semi-supervised Learning |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Interpreting and Evaluating Neural Network Robustness |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Iterative Budgeted Exponential Search |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Joint Link Prediction and Network Alignment via Cross-graph Embedding |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| K-Core Maximization: An Edge Addition Approach |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection |
✅ |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
5 |
| KCNN: Kernel-wise Quantization to Remarkably Decrease Multiplications in Convolutional Neural Network |
✅ |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
5 |
| KitcheNette: Predicting and Ranking Food Ingredient Pairings using Siamese Neural Network |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Knowledge Aware Semantic Concept Expansion for Image-Text Matching |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Knowledge Base Question Answering with Topic Units |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Knowledge-enhanced Hierarchical Attention for Community Question Answering with Multi-task and Adaptive Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Knowledgeable Storyteller: A Commonsense-Driven Generative Model for Visual Storytelling |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| LRDNN: Local-refining based Deep Neural Network for Person Re-Identification with Attribute Discerning |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| LTL and Beyond: Formal Languages for Reward Function Specification in Reinforcement Learning |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
3 |
| Label Distribution Learning with Label Correlations via Low-Rank Approximation |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Label distribution learning with label-specific features |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Landmark Selection for Zero-shot Learning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Large Scale Evolving Graphs with Burst Detection |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Large-Scale Home Energy Management Using Entropy-Based Collective Multiagent Deep Reinforcement Learning Framework |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Latent Distribution Preserving Deep Subspace Clustering |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Latent Semantics Encoding for Label Distribution Learning |
✅ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
6 |
| Leadership in Congestion Games: Multiple User Classes and Non-Singleton Actions |
❌ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
3 |
| Leap-LSTM: Enhancing Long Short-Term Memory for Text Categorization |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learn Smart with Less: Building Better Online Decision Trees with Fewer Training Examples |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Learn to Select via Hierarchical Gate Mechanism for Aspect-Based Sentiment Analysis |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning Assistance from an Adversarial Critic for Multi-Outputs Prediction |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning Deep Decentralized Policy Network by Collective Rewards for Real-Time Combat Game |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Learning Description Logic Concepts: When can Positive and Negative Examples be Separated? |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Learning Disentangled Semantic Representation for Domain Adaptation |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Learning Generative Adversarial Networks from Multiple Data Sources |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Learning Hierarchical Symbolic Representations to Support Interactive Task Learning and Knowledge Transfer |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
3 |
| Learning Image-Specific Attributes by Hyperbolic Neighborhood Graph Propagation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Learning Instance-wise Sparsity for Accelerating Deep Models |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Learning Interpretable Deep State Space Model for Probabilistic Time Series Forecasting |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Learning Interpretable Relational Structures of Hinge-loss Markov Random Fields |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning K-way D-dimensional Discrete Embedding for Hierarchical Data Visualization and Retrieval |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Learning Low-precision Neural Networks without Straight-Through Estimator (STE) |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
3 |
| Learning Multi-Objective Rewards and User Utility Function in Contextual Bandits for Personalized Ranking |
❌ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
4 |
| Learning Multiple Maps from Conditional Ordinal Triplets |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Learning Network Embedding with Community Structural Information |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Learning Relational Representations with Auto-encoding Logic Programs |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning Robust Distance Metric with Side Information via Ratio Minimization of Orthogonally Constrained L21-Norm Distances |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Learning Semantic Annotations for Tabular Data |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Learning Shared Knowledge for Deep Lifelong Learning using Deconvolutional Networks |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| Learning Shared Vertex Representation in Heterogeneous Graphs with Convolutional Networks for Recommendation |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Learning Sound Events from Webly Labeled Data |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Learning Strictly Orthogonal p-Order Nonnegative Laplacian Embedding via Smoothed Iterative Reweighted Method |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Learning Swarm Behaviors using Grammatical Evolution and Behavior Trees |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Learning Task-Specific Representation for Novel Words in Sequence Labeling |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Learning Topic Models by Neighborhood Aggregation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning Unsupervised Visual Grounding Through Semantic Self-Supervision |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Learning a Generative Model for Fusing Infrared and Visible Images via Conditional Generative Adversarial Network with Dual Discriminators |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Learning for Tail Label Data: A Label-Specific Feature Approach |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Learning to Draw Text in Natural Images with Conditional Adversarial Networks |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Learning to Interpret Satellite Images using Wikipedia |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning to Learn Gradient Aggregation by Gradient Descent |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Learning to Select Knowledge for Response Generation in Dialog Systems |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Learning towards Abstractive Timeline Summarization |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Legal Judgment Prediction via Multi-Perspective Bi-Feedback Network |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Lifted Message Passing for Hybrid Probabilistic Inference |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
6 |
| Light-Weight Hybrid Convolutional Network for Liver Tumor Segmentation |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Linear Time Complexity Time Series Clustering with Symbolic Pattern Forest |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Local Search with Efficient Automatic Configuration for Minimum Vertex Cover |
✅ |
✅ |
✅ |
✅ |
✅ |
✅ |
✅ |
7 |
| Localizing Unseen Activities in Video via Image Query |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Locate-Then-Detect: Real-time Web Attack Detection via Attention-based Deep Neural Networks |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| LogAnomaly: Unsupervised Detection of Sequential and Quantitative Anomalies in Unstructured Logs |
❌ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
4 |
| Low Shot Box Correction for Weakly Supervised Object Detection |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Low-Bit Quantization for Attributed Network Representation Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Lower Bound of Locally Differentially Private Sparse Covariance Matrix Estimation |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| MAT-Net: Medial Axis Transform Network for 3D Object Recognition |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| MEGAN: A Generative Adversarial Network for Multi-View Network Embedding |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| MINA: Multilevel Knowledge-Guided Attention for Modeling Electrocardiography Signals |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
✅ |
6 |
| MLRDA: A Multi-Task Semi-Supervised Learning Framework for Drug-Drug Interaction Prediction |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| MNN: Multimodal Attentional Neural Networks for Diagnosis Prediction |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
✅ |
3 |
| MR-GNN: Multi-Resolution and Dual Graph Neural Network for Predicting Structured Entity Interactions |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| MSR: Multi-Scale Shape Regression for Scene Text Detection |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| MUSICAL: Multi-Scale Image Contextual Attention Learning for Inpainting |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Margin Learning Embedded Prediction for Video Anomaly Detection with A Few Anomalies |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Marginal Posterior Sampling for Slate Bandits |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Mask and Infill: Applying Masked Language Model for Sentiment Transfer |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Masked Graph Convolutional Network |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| Matching User with Item Set: Collaborative Bundle Recommendation with Deep Attention Network |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Matrix Completion in the Unit Hypercube via Structured Matrix Factorization |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Maximin-Aware Allocations of Indivisible Goods |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Measuring Structural Similarities in Finite MDPs |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Measuring the Likelihood of Numerical Constraints |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Medical Concept Embedding with Multiple Ontological Representations |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Medical Concept Representation Learning from Multi-source Data |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Merge-and-Shrink Task Reformulation for Classical Planning |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Meta Reinforcement Learning with Task Embedding and Shared Policy |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
2 |
| Meta-Learning for Low-resource Natural Language Generation in Task-oriented Dialogue Systems |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Metadata-driven Task Relation Discovery for Multi-task Learning |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Metatrace Actor-Critic: Online Step-Size Tuning by Meta-gradient Descent for Reinforcement Learning Control |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Metric Learning on Healthcare Data with Incomplete Modalities |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| MiSC: Mixed Strategies Crowdsourcing |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Mindful Active Learning |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| MineRL: A Large-Scale Dataset of Minecraft Demonstrations |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Minimizing Time-to-Rank: A Learning and Recommendation Approach |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Mixed-World Reasoning with Existential Rules under Active-Domain Semantics |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Model-Agnostic Adversarial Detection by Random Perturbations |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
4 |
| Model-Based Diagnosis with Multiple Observations |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
6 |
| Model-Free Model Reconciliation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| Modeling Multi-Purpose Sessions for Next-Item Recommendations via Mixture-Channel Purpose Routing Networks |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Modeling Noisy Hierarchical Types in Fine-Grained Entity Typing: A Content-Based Weighting Approach |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Modeling Source Syntax and Semantics for Neural AMR Parsing |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Modeling both Context- and Speaker-Sensitive Dependence for Emotion Detection in Multi-speaker Conversations |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Monitoring of a Dynamic System Based on Autoencoders |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
3 |
| Monte Carlo Tree Search for Policy Optimization |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Motion Invariance in Visual Environments |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Multi-Agent Pathfinding with Continuous Time |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Multi-Class Learning using Unlabeled Samples: Theory and Algorithm |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Multi-Domain Sentiment Classification Based on Domain-Aware Embedding and Attention |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Multi-Group Encoder-Decoder Networks to Fuse Heterogeneous Data for Next-Day Air Quality Prediction |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Multi-Level Visual-Semantic Alignments with Relation-Wise Dual Attention Network for Image and Text Matching |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Multi-Margin based Decorrelation Learning for Heterogeneous Face Recognition |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Multi-Objective Generalized Linear Bandits |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Multi-Population Congestion Games With Incomplete Information |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Multi-Prototype Networks for Unconstrained Set-based Face Recognition |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Multi-Robot Planning Under Uncertain Travel Times and Safety Constraints |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Multi-View Active Learning for Video Recommendation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Multi-View Multi-Label Learning with View-Specific Information Extraction |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Multi-View Multiple Clustering |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Multi-agent Attentional Activity Recognition |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Multi-scale Information Diffusion Prediction with Reinforced Recurrent Networks |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Multi-view Clustering via Late Fusion Alignment Maximization |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Multi-view Knowledge Graph Embedding for Entity Alignment |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Multi-view Spectral Clustering Network |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Multigoal Committee Selection |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Multiple Noisy Label Distribution Propagation for Crowdsourcing |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Multiple Partitions Aligned Clustering |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Multiple Policy Value Monte Carlo Tree Search |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Multiplicative Sparse Feature Decomposition for Efficient Multi-View Multi-Task Learning |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Musical Composition Style Transfer via Disentangled Timbre Representations |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Mutually Reinforced Spatio-Temporal Convolutional Tube for Human Action Recognition |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Neighborhood-Aware Attentional Representation for Multilingual Knowledge Graphs |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Network Embedding under Partial Monitoring for Evolving Networks |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Network Embedding with Dual Generation Tasks |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Network Formation under Random Attack and Probabilistic Spread |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Network-Specific Variational Auto-Encoder for Embedding in Attribute Networks |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Neural Collective Entity Linking Based on Recurrent Random Walk Network Learning |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Neural Network based Continuous Conditional Random Field for Fine-grained Crime Prediction |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Neural Networks for Predicting Human Interactions in Repeated Games |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
4 |
| Neural News Recommendation with Attentive Multi-View Learning |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Neural Program Induction for KBQA Without Gold Programs or Query Annotations |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
4 |
| Neurons Merging Layer: Towards Progressive Redundancy Reduction for Deep Supervised Hashing |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Node Embedding over Temporal Graphs |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Noise-Resilient Similarity Preserving Network Embedding for Social Networks |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Non-smooth Optimization over Stiefel Manifolds with Applications to Dimensionality Reduction and Graph Clustering |
✅ |
❌ |
✅ |
❌ |
❌ |
✅ |
✅ |
4 |
| Nostalgic Adam: Weighting More of the Past Gradients When Designing the Adaptive Learning Rate |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
✅ |
5 |
| Novel Collaborative Filtering Recommender Friendly to Privacy Protection |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Nuclei Segmentation via a Deep Panoptic Model with Semantic Feature Fusion |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Object Detection based Deep Unsupervised Hashing |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Oblivious and Semi-Oblivious Boundedness for Existential Rules |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Observations on Darwiche and Pearl's Approach for Iterated Belief Revision |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Obstacle Tower: A Generalization Challenge in Vision, Control, and Planning |
❌ |
✅ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Omnidirectional Scene Text Detection with Sequential-free Box Discretization |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| On Computational Complexity of Pickup-and-Delivery Problems with Precedence Constraints or Time Windows |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| On Computational Tractability for Rational Verification |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| On Constrained Open-World Probabilistic Databases |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| On Division Versus Saturation in Pseudo-Boolean Solving |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| On Finite and Unrestricted Query Entailment beyond SQ with Number Restrictions on Transitive Roles |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| On Principled Entropy Exploration in Policy Optimization |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| On Privacy Protection of Latent Dirichlet Allocation Model Training |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| On Retrospecting Human Dynamics with Attention |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| On Strategyproof Conference Peer Review |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| On Succinct Encodings for the Tournament Fixing Problem |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| On the Convergence of (Stochastic) Gradient Descent with Extrapolation for Non-Convex Minimization |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| On the Effectiveness of Low Frequency Perturbations |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| On the Efficiency and Equilibria of Rich Ads |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| On the Estimation of Treatment Effect with Text Covariates |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| On the Integration of CP-nets in ASPRIN |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| On the Problem of Assigning PhD Grants |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| On the Tree Representations of Dichotomous Preferences |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| One Network for Multi-Domains: Domain Adaptive Hashing with Intersectant Generative Adversarial Networks |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| One-Shot Texture Retrieval with Global Context Metric |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Online Learning from Capricious Data Streams: A Generative Approach |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Online Probabilistic Goal Recognition over Nominal Models |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Ontology Approximation in Horn Description Logics |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Open-Ended Long-Form Video Question Answering via Hierarchical Convolutional Self-Attention Networks |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Optimal Exploitation of Clustering and History Information in Multi-armed Bandit |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Optimality and Nash Stability in Additive Separable Generalized Group Activity Selection Problems |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Optimizing Constraint Solving via Dynamic Programming |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Ornstein Auto-Encoders |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Out of Sight But Not Out of Mind: An Answer Set Programming Based Online Abduction Framework for Visual Sensemaking in Autonomous Driving |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Out-of-sample Node Representation Learning for Heterogeneous Graph in Real-time Android Malware Detection |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Outlier Detection for Time Series with Recurrent Autoencoder Ensembles |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Outlier-Robust Multi-Aspect Streaming Tensor Completion and Factorization |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| PD-GAN: Adversarial Learning for Personalized Diversity-Promoting Recommendation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| PI-Bully: Personalized Cyberbullying Detection with Peer Influence |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| PRoFET: Predicting the Risk of Firms from Event Transcripts |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
✅ |
5 |
| Parallel Wasserstein Generative Adversarial Nets with Multiple Discriminators |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Parametric Manifold Learning of Gaussian Mixture Models |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Partial Label Learning by Semantic Difference Maximization |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Partial Label Learning with Unlabeled Data |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Partitioning Techniques in LTLf Synthesis |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Parts4Feature: Learning 3D Global Features from Generally Semantic Parts in Multiple Views |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Patent Citation Dynamics Modeling via Multi-Attention Recurrent Networks |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Path Planning with CPD Heuristics |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Pedestrian Attribute Recognition by Joint Visual-semantic Reasoning and Knowledge Distillation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Perception-Aware Point-Based Value Iteration for Partially Observable Markov Decision Processes |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Persistence Bag-of-Words for Topological Data Analysis |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Personalized Multimedia Item and Key Frame Recommendation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Perturbed-History Exploration in Stochastic Multi-Armed Bandits |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Phase Transition Behavior of Cardinality and XOR Constraints |
❌ |
✅ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Pivotal Relationship Identification: The K-Truss Minimization Problem |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Planning for LTLf /LDLf Goals in Non-Markovian Fully Observable Nondeterministic Domains |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Planning with Expectation Models |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Play and Prune: Adaptive Filter Pruning for Deep Model Compression |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Playgol: Learning Programs Through Play |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Playing Card-Based RTS Games with Deep Reinforcement Learning |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Playing FPS Games With Environment-Aware Hierarchical Reinforcement Learning |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
3 |
| Polygon-Net: A General Framework for Jointly Boosting Multiple Unsupervised Neural Machine Translation Models |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Portioning Using Ordinal Preferences: Fairness and Efficiency |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Pose-preserving Cross Spectral Face Hallucination |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Position Focused Attention Network for Image-Text Matching |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Positive and Unlabeled Learning with Label Disambiguation |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Possibilistic Games with Incomplete Information |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Pre-training of Graph Augmented Transformers for Medication Recommendation |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Predict+Optimise with Ranking Objectives: Exhaustively Learning Linear Functions |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Predicting dominance in multi-person videos |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Predicting the Visual Focus of Attention in Multi-Person Discussion Videos |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Prediction of Mild Cognitive Impairment Conversion Using Auxiliary Information |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Preferences Single-Peaked on a Tree: Sampling and Tree Recognition |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Preferred Deals in General Environments |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Principal Component Analysis in the Local Differential Privacy Model |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Priority Inheritance with Backtracking for Iterative Multi-agent Path Finding |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Privacy-Preserving Obfuscation of Critical Infrastructure Networks |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Privacy-aware Synthesizing for Crowdsourced Data |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| ProNE: Fast and Scalable Network Representation Learning |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Probabilistic Strategy Logic |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Procedural Generation of Initial States of Sokoban |
❌ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
2 |
| Profit-driven Task Assignment in Spatial Crowdsourcing |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Progressive Transfer Learning for Person Re-identification |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Protecting Elections by Recounting Ballots |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph |
✅ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
6 |
| Pseudo Supervised Matrix Factorization in Discriminative Subspace |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Quantum-Inspired Interactive Networks for Conversational Sentiment Analysis |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Quaternion Collaborative Filtering for Recommendation |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| RDPD: Rich Data Helps Poor Data via Imitation |
✅ |
✅ |
✅ |
✅ |
✅ |
✅ |
✅ |
7 |
| RLTM: An Efficient Neural IR Framework for Long Documents |
✅ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| RTHN: A RNN-Transformer Hierarchical Network for Emotion Cause Extraction |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Randomized Adversarial Imitation Learning for Autonomous Driving |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Randomized Greedy Search for Structured Prediction: Amortized Inference and Learning |
✅ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
6 |
| Ranked Programming |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Rapid Performance Gain through Active Model Reuse |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Rational Inference Relations from Maximal Consistent Subsets Selection |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Reachability Games in Dynamic Epistemic Logic |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Reachability and Coverage Planning for Connected Agents |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Reading selectively via Binary Input Gated Recurrent Unit |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Real-Time Adversarial Attacks |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Reallocating Multiple Facilities on the Line |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Reasoning about Disclosure in Data Integration in the Presence of Source Constraints |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Reasoning about Quality and Fuzziness of Strategic Behaviours |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| RecoNet: An Interpretable Neural Architecture for Recommender Systems |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| Recommending Links to Maximize the Influence in Social Networks |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Recurrent Existence Determination Through Policy Optimization |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Recurrent Generative Networks for Multi-Resolution Satellite Data: An Application in Cropland Monitoring |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Recurrent Neural Network for Text Classification with Hierarchical Multiscale Dense Connections |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Refining Word Representations by Manifold Learning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Regarding Jump Point Search and Subgoal Graphs |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
3 |
| Region Deformer Networks for Unsupervised Depth Estimation from Unconstrained Monocular Videos |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Regular Decision Processes: A Model for Non-Markovian Domains |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Reinforced Negative Sampling for Recommendation with Exposure Data |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Reinforcement Learning Experience Reuse with Policy Residual Representation |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Relation Extraction Using Supervision from Topic Knowledge of Relation Labels |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Reparameterizable Subset Sampling via Continuous Relaxations |
✅ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
6 |
| Representation Learning with Weighted Inner Product for Universal Approximation of General Similarities |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Representation Learning-Assisted Click-Through Rate Prediction |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Resolution and Domination: An Improved Exact MaxSAT Algorithm |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Resolution-invariant Person Re-Identification |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Rethinking Loss Design for Large-scale 3D Shape Retrieval |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Revealing Semantic Structures of Texts: Multi-grained Framework for Automatic Mind-map Generation |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Revisiting Controlled Query Evaluation in Description Logics |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Reward Learning for Efficient Reinforcement Learning in Extractive Document Summarisation |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Ridesharing with Driver Location Preferences |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Risk Assessment for Networked-guarantee Loans Using High-order Graph Attention Representation |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Robust Audio Adversarial Example for a Physical Attack |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Robust Embedding with Multi-Level Structures for Link Prediction |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Robust Flexible Feature Selection via Exclusive L21 Regularization |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Robust Learning from Noisy Side-information by Semidefinite Programming |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Robust Low-Tubal-Rank Tensor Completion via Convex Optimization |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| RobustTrend: A Huber Loss with a Combined First and Second Order Difference Regularization for Time Series Trend Filtering |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Robustness against Agent Failure in Hedonic Games |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Robustra: Training Provable Robust Neural Networks over Reference Adversarial Space |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| SPAGAN: Shortest Path Graph Attention Network |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| SPINE: Structural Identity Preserved Inductive Network Embedding |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| STCA: Spatio-Temporal Credit Assignment with Delayed Feedback in Deep Spiking Neural Networks |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
3 |
| STG2Seq: Spatial-Temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
✅ |
3 |
| Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Satisfaction and Implication of Integrity Constraints in Ontology-based Data Access |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Scalable Bayesian Non-linear Matrix Completion |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Scalable Block-Diagonal Locality-Constrained Projective Dictionary Learning |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Scalable Semi-Supervised SVM via Triply Stochastic Gradients |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Scaling Fine-grained Modularity Clustering for Massive Graphs |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Scheduling Jobs with Stochastic Processing Time on Parallel Identical Machines |
✅ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
4 |
| Schelling Games on Graphs |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Scribble-to-Painting Transformation with Multi-Task Generative Adversarial Networks |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Self-attentive Biaffine Dependency Parsing |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Semantic Characterization of Data Services through Ontologies |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Semi-supervised Three-dimensional Reconstruction Framework with GAN |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Semi-supervised User Profiling with Heterogeneous Graph Attention Networks |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Sentiment-Controllable Chinese Poetry Generation |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Sequence Generation: From Both Sides to the Middle |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Sequential and Diverse Recommendation with Long Tail |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| Sharing Attention Weights for Fast Transformer |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Sharing Experience in Multitask Reinforcement Learning |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Similarity Preserving Representation Learning for Time Series Clustering |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Simple Conditionals with Constrained Right Weakening |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Simultaneous Prediction Intervals for Patient-Specific Survival Curves |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Simultaneous Representation Learning and Clustering for Incomplete Multi-view Data |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Single-Channel Signal Separation and Deconvolution with Generative Adversarial Networks |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Sketched Iterative Algorithms for Structured Generalized Linear Models |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| SlateQ: A Tractable Decomposition for Reinforcement Learning with Recommendation Sets |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Soft Policy Gradient Method for Maximum Entropy Deep Reinforcement Learning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Solving Continual Combinatorial Selection via Deep Reinforcement Learning |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Solving the Satisfiability Problem of Modal Logic S5 Guided by Graph Coloring |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
6 |
| Some Things are Easier for the Dumb and the Bright Ones (Beware the Average!) |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| SparseSense: Human Activity Recognition from Highly Sparse Sensor Data-streams Using Set-based Neural Networks |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Spatio-Temporal Attentive RNN for Node Classification in Temporal Attributed Graphs |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Spectral Perturbation Meets Incomplete Multi-view Data |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Spotting Collective Behaviour of Online Frauds in Customer Reviews |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Stable and Envy-free Partitions in Hedonic Games |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Statistical Guarantees for the Robustness of Bayesian Neural Networks |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Steady-State Policy Synthesis for Verifiable Control |
❌ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
3 |
| Stochastic Constraint Propagation for Mining Probabilistic Networks |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Story Ending Prediction by Transferable BERT |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Strategic Signaling for Selling Information Goods |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Strategy Logic with Simple Goals: Tractable Reasoning about Strategies |
✅ |
✅ |
❌ |
❌ |
✅ |
❌ |
✅ |
4 |
| Strategyproof and Approximately Maxmin Fair Share Allocation of Chores |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Stratified Evidence Logics |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Strong Fully Observable Non-Deterministic Planning with LTL and LTLf Goals |
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✅ |
❌ |
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2 |
| Structure Learning for Safe Policy Improvement |
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3 |
| Structure-Aware Residual Pyramid Network for Monocular Depth Estimation |
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3 |
| Subgoal-Based Temporal Abstraction in Monte-Carlo Tree Search |
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4 |
| Submodular Batch Selection for Training Deep Neural Networks |
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4 |
| Success Prediction on Crowdfunding with Multimodal Deep Learning |
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4 |
| Successor Options: An Option Discovery Framework for Reinforcement Learning |
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3 |
| Supervised Set-to-Set Hashing in Visual Recognition |
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3 |
| Supervised Short-Length Hashing |
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4 |
| Swarm Engineering Through Quantitative Measurement of Swarm Robotic Principles in a 10,000 Robot Swarm |
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2 |
| Swell-and-Shrink: Decomposing Image Captioning by Transformation and Summarization |
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✅ |
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3 |
| Sybil-Resilient Reality-Aware Social Choice |
✅ |
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1 |
| SynthNet: Learning to Synthesize Music End-to-End |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Synthesizing Datalog Programs using Numerical Relaxation |
✅ |
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✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Systematic Conservation Planning for Sustainable Land-use Policies: A Constrained Partitioning Approach to Reserve Selection and Design. |
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✅ |
✅ |
❌ |
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❌ |
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4 |
| T-CVAE: Transformer-Based Conditioned Variational Autoencoder for Story Completion |
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✅ |
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❌ |
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✅ |
4 |
| Tag2Gauss: Learning Tag Representations via Gaussian Distribution in Tagged Networks |
✅ |
❌ |
✅ |
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❌ |
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✅ |
4 |
| Talking Face Generation by Conditional Recurrent Adversarial Network |
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✅ |
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✅ |
❌ |
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4 |
| Taming the Noisy Gradient: Train Deep Neural Networks with Small Batch Sizes |
✅ |
✅ |
✅ |
❌ |
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✅ |
4 |
| Temporal Information Design in Contests |
❌ |
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❌ |
❌ |
❌ |
❌ |
0 |
| Temporal Pyramid Pooling Convolutional Neural Network for Cover Song Identification |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| The Complexity of Model Checking Knowledge and Time |
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❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations |
✅ |
✅ |
✅ |
❌ |
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❌ |
✅ |
4 |
| The Expected-Length Model of Options |
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❌ |
❌ |
❌ |
✅ |
1 |
| The Interplay of Emotions and Norms in Multiagent Systems |
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❌ |
✅ |
❌ |
❌ |
❌ |
1 |
| The Parameterized Complexity of Motion Planning for Snake-Like Robots |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| The Price of Fairness for Indivisible Goods |
❌ |
❌ |
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❌ |
❌ |
❌ |
❌ |
0 |
| The Price of Governance: A Middle Ground Solution to Coordination in Organizational Control |
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❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| The Price of Local Fairness in Multistage Selection |
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✅ |
✅ |
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2 |
| The Pupil Has Become the Master: Teacher-Student Model-Based Word Embedding Distillation with Ensemble Learning |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Theoretical Investigation of Generalization Bound for Residual Networks |
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1 |
| Thompson Sampling on Symmetric Alpha-Stable Bandits |
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✅ |
2 |
| Three-Player Wasserstein GAN via Amortised Duality |
✅ |
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4 |
| Three-quarter Sibling Regression for Denoising Observational Data |
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✅ |
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❌ |
❌ |
❌ |
1 |
| Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective |
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✅ |
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4 |
| Topology Optimization based Graph Convolutional Network |
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3 |
| Toward Efficient Navigation of Massive-Scale Geo-Textual Streams |
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3 |
| Towards Discriminative Representation Learning for Speech Emotion Recognition |
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4 |
| Towards Efficient Detection and Optimal Response against Sophisticated Opponents |
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✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Towards Robust ResNet: A Small Step but a Giant Leap |
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❌ |
✅ |
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2 |
| TransMS: Knowledge Graph Embedding for Complex Relations by Multidirectional Semantics |
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✅ |
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3 |
| Transfer of Temporal Logic Formulas in Reinforcement Learning |
✅ |
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2 |
| Transferable Adversarial Attacks for Image and Video Object Detection |
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✅ |
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2 |
| Travel Time Estimation without Road Networks: An Urban Morphological Layout Representation Approach |
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✅ |
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1 |
| Tree Sampling Divergence: An Information-Theoretic Metric for Hierarchical Graph Clustering |
✅ |
✅ |
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3 |
| Trend-Aware Tensor Factorization for Job Skill Demand Analysis |
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1 |
| Triplet Enhanced AutoEncoder: Model-free Discriminative Network Embedding |
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4 |
| Truly Batch Apprenticeship Learning with Deep Successor Features |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Twin-Systems to Explain Artificial Neural Networks using Case-Based Reasoning: Comparative Tests of Feature-Weighting Methods in ANN-CBR Twins for XAI |
✅ |
✅ |
✅ |
❌ |
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5 |
| Two-Stage Generative Models of Simulating Training Data at The Voxel Level for Large-Scale Microscopy Bioimage Segmentation |
❌ |
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2 |
| Unified Embedding Model over Heterogeneous Information Network for Personalized Recommendation |
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3 |
| Unifying Search-based and Compilation-based Approaches to Multi-agent Path Finding through Satisfiability Modulo Theories |
✅ |
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6 |
| Unifying the Stochastic and the Adversarial Bandits with Knapsack |
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1 |
| Unit Selection Based on Counterfactual Logic |
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0 |
| Unobserved Is Not Equal to Non-existent: Using Gaussian Processes to Infer Immediate Rewards Across Contexts |
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1 |
| Unsupervised Embedding Enhancements of Knowledge Graphs using Textual Associations |
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4 |
| Unsupervised Hierarchical Temporal Abstraction by Simultaneously Learning Expectations and Representations |
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3 |
| Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity |
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✅ |
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2 |
| Unsupervised Learning of Monocular Depth and Ego-Motion using Conditional PatchGANs |
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4 |
| Unsupervised Learning of Scene Flow Estimation Fusing with Local Rigidity |
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4 |
| Unsupervised Neural Aspect Extraction with Sememes |
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2 |
| Using Natural Language for Reward Shaping in Reinforcement Learning |
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3 |
| Utilizing Non-Parallel Text for Style Transfer by Making Partial Comparisons |
✅ |
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✅ |
❌ |
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6 |
| VAEGAN: A Collaborative Filtering Framework based on Adversarial Variational Autoencoders |
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❌ |
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3 |
| Value Function Transfer for Deep Multi-Agent Reinforcement Learning Based on N-Step Returns |
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2 |
| Variation Generalized Feature Learning via Intra-view Variation Adaptation |
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✅ |
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3 |
| Variational Graph Embedding and Clustering with Laplacian Eigenmaps |
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2 |
| Video Interactive Captioning with Human Prompts |
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4 |
| VulSniper: Focus Your Attention to Shoot Fine-Grained Vulnerabilities |
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3 |
| Weak Supervision Enhanced Generative Network for Question Generation |
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3 |
| Weakly Supervised Multi-Label Learning via Label Enhancement |
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3 |
| Weakly Supervised Multi-task Learning for Semantic Parsing |
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3 |
| Weighted Maxmin Fair Share Allocation of Indivisible Chores |
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1 |
| What Has Been Said? Identifying the Change Formula in a Belief Revision Scenario |
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1 |
| What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features |
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2 |
| Who Should Pay the Cost: A Game-theoretic Model for Government Subsidized Investments to Improve National Cybersecurity |
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4 |
| Why Can’t You Do That HAL? Explaining Unsolvability of Planning Tasks |
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2 |
| Worst-Case Discriminative Feature Selection |
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3 |
| Worst-Case Optimal Querying of Very Expressive Description Logics with Path Expressions and Succinct Counting |
❌ |
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❌ |
0 |
| Zero-shot Learning with Many Classes by High-rank Deep Embedding Networks |
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✅ |
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✅ |
2 |
| Zero-shot Metric Learning |
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5 |
| Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization |
✅ |
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❌ |
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3 |
| iDev: Enhancing Social Coding Security by Cross-platform User Identification Between GitHub and Stack Overflow |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| mdfa: Multi-Differential Fairness Auditor for Black Box Classifiers |
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✅ |
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❌ |
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4 |