| 280 Birds With One Stone: Inducing Multilingual Taxonomies From Wikipedia Using Character-Level Classification |
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❌ |
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5 |
| 3D Box Proposals From a Single Monocular Image of an Indoor Scene |
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4 |
| A Batch Learning Framework for Scalable Personalized Ranking |
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6 |
| A Bayesian Clearing Mechanism for Combinatorial Auctions |
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2 |
| A Cascaded Inception of Inception Network With Attention Modulated Feature Fusion for Human Pose Estimation |
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3 |
| A Change-Detection Based Framework for Piecewise-Stationary Multi-Armed Bandit Problem |
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3 |
| A Combinatorial-Bandit Algorithm for the Online Joint Bid/Budget Optimization of Pay-per-Click Advertising Campaigns |
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5 |
| A Continuous Relaxation of Beam Search for End-to-End Training of Neural Sequence Models |
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4 |
| A Coverage-Based Utility Model for Identifying Unknown Unknowns |
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5 |
| A Deep Cascade Network for Unaligned Face Attribute Classification |
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3 |
| A Deep Generative Framework for Paraphrase Generation |
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3 |
| A Deep Model With Local Surrogate Loss for General Cost-Sensitive Multi-Label Learning |
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4 |
| A Deep Ranking Model for Spatio-Temporal Highlight Detection From a 360◦ Video |
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3 |
| A Framework and Positive Results for IAR-answering |
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3 |
| A Framework for Multistream Regression With Direct Density Ratio Estimation |
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3 |
| A General Formulation for Safely Exploiting Weakly Supervised Data |
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4 |
| A Knowledge-Grounded Neural Conversation Model |
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2 |
| A Low-Cost Ethics Shaping Approach for Designing Reinforcement Learning Agents |
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1 |
| A Multi-Task Learning Approach for Improving Product Title Compression with User Search Log Data |
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3 |
| A Multi-View Fusion Neural Network for Answer Selection |
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3 |
| A Multilayer Convolutional Encoder-Decoder Neural Network for Grammatical Error Correction |
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5 |
| A Network-Specific Markov Random Field Approach to Community Detection |
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3 |
| A Neural Attention Model for Urban Air Quality Inference: Learning the Weights of Monitoring Stations |
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3 |
| A Neural Stochastic Volatility Model |
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5 |
| A Neural Transition-Based Approach for Semantic Dependency Graph Parsing |
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5 |
| A Parallelizable Acceleration Framework for Packing Linear Programs |
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3 |
| A Plasticity-Centric Approach to Train the Non-Differential Spiking Neural Networks |
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3 |
| A Poisson Gamma Probabilistic Model for Latent Node-Group Memberships in Dynamic Networks |
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4 |
| A Probabilistic Hierarchical Model for Multi-View and Multi-Feature Classification |
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4 |
| A Provable Approach for Double-Sparse Coding |
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3 |
| A Question-Focused Multi-Factor Attention Network for Question Answering |
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4 |
| A Recursive Algorithm to Generate Balanced Weekend Tournaments |
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0 |
| A Recursive Scenario Decomposition Algorithm for Combinatorial Multistage Stochastic Optimisation Problems |
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✅ |
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4 |
| A Regression Approach for Modeling Games With Many Symmetric Players |
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1 |
| A SAT+CAS Method for Enumerating Williamson Matrices of Even Order |
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✅ |
❌ |
❌ |
1 |
| A Semantic QA-Based Approach for Text Summarization Evaluation |
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2 |
| A Spherical Hidden Markov Model for Semantics-Rich Human Mobility Modeling |
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3 |
| A Two-Stage MaxSAT Reasoning Approach for the Maximum Weight Clique Problem |
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6 |
| A Unified Model for Document-Based Question Answering Based on Human-Like Reading Strategy |
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4 |
| A Voting-Based System for Ethical Decision Making |
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1 |
| AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games |
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1 |
| AJILE Movement Prediction: Multimodal Deep Learning for Natural Human Neural Recordings and Video |
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4 |
| AMR Parsing With Cache Transition Systems |
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3 |
| ARC: Adversarial Robust Cuts for Semi-Supervised and Multi-Label Classification |
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3 |
| ATRank: An Attention-Based User Behavior Modeling Framework for Recommendation |
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2 |
| Accelerated Best-First Search With Upper-Bound Computation for Submodular Function Maximization |
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4 |
| Accelerated Method for Stochastic Composition Optimization With Nonsmooth Regularization |
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2 |
| Accelerated Training for Massive Classification via Dynamic Class Selection |
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4 |
| Acquiring Common Sense Spatial Knowledge Through Implicit Spatial Templates |
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5 |
| Action Branching Architectures for Deep Reinforcement Learning |
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2 |
| Action Prediction From Videos via Memorizing Hard-to-Predict Samples |
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3 |
| Action Recognition From Skeleton Data via Analogical Generalization Over Qualitative Representations |
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3 |
| Action Recognition With Coarse-to-Fine Deep Feature Integration and Asynchronous Fusion |
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3 |
| Action Schema Networks: Generalised Policies With Deep Learning |
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5 |
| Actionable Email Intent Modeling With Reparametrized RNNs |
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2 |
| Active Lifelong Learning With “Watchdog” |
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4 |
| AdaComp : Adaptive Residual Gradient Compression for Data-Parallel Distributed Training |
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4 |
| AdaFlock: Adaptive Feature Discovery for Human-in-the-loop Predictive Modeling |
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3 |
| Adapting a Kidney Exchange Algorithm to Align With Human Values |
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3 |
| Adaptive Co-attention Network for Named Entity Recognition in Tweets |
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2 |
| Adaptive Feature Abstraction for Translating Video to Text |
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3 |
| Adaptive Graph Convolutional Neural Networks |
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3 |
| Adaptive Quantization for Deep Neural Network |
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5 |
| Addressee and Response Selection in Multi-Party Conversations With Speaker Interaction RNNs |
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4 |
| Adversarial Discriminative Heterogeneous Face Recognition |
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3 |
| Adversarial Dropout for Supervised and Semi-Supervised Learning |
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4 |
| Adversarial Learning for Chinese NER From Crowd Annotations |
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2 |
| Adversarial Learning of Portable Student Networks |
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4 |
| Adversarial Network Embedding |
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2 |
| Adversarial Zero-shot Learning With Semantic Augmentation |
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❌ |
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3 |
| Algorithms for Generalized Topic Modeling |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Algorithms for Trip-Vehicle Assignment in Ride-Sharing |
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❌ |
❌ |
❌ |
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2 |
| Allocation Problems in Ride-Sharing Platforms: Online Matching With Offline Reusable Resources |
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✅ |
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3 |
| Alternating Circulant Random Features for Semigroup Kernels |
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4 |
| Alternating Optimisation and Quadrature for Robust Control |
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❌ |
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1 |
| An AI Planning Solution to Scenario Generation for Enterprise Risk Management |
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2 |
| An Adversarial Hierarchical Hidden Markov Model for Human Pose Modeling and Generation |
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✅ |
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5 |
| An Ant-Based Algorithm to Solve Distributed Constraint Optimization Problems |
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2 |
| An Axiomatization of the Eigenvector and Katz Centralities |
❌ |
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❌ |
❌ |
❌ |
❌ |
0 |
| An Efficient, Expressive and Local Minima-Free Method for Learning Controlled Dynamical Systems |
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✅ |
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4 |
| An End-to-End Deep Learning Architecture for Graph Classification |
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4 |
| An Euclidean Distance Based on Tensor Product Graph Diffusion Related Attribute Value Embedding for Nominal Data Clustering |
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3 |
| An Experimental Study of Advice in Sequential Decision-Making Under Uncertainty |
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2 |
| An Interactive Multi-Label Consensus Labeling Model for Multiple Labeler Judgments |
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3 |
| An Interpretable Generative Adversarial Approach to Classification of Latent Entity Relations in Unstructured Sentences |
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2 |
| An Interpretable Joint Graphical Model for Fact-Checking From Crowds |
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5 |
| An Optimal Online Method of Selecting Source Policies for Reinforcement Learning |
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2 |
| An Unsupervised Model With Attention Autoencoders for Question Retrieval |
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❌ |
✅ |
✅ |
❌ |
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3 |
| Anchors: High-Precision Model-Agnostic Explanations |
✅ |
✅ |
✅ |
✅ |
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5 |
| Answering Regular Path Queries over SQ Ontologies |
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❌ |
❌ |
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0 |
| Anti-Makeup: Learning A Bi-Level Adversarial Network for Makeup-Invariant Face Verification |
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❌ |
✅ |
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3 |
| Anytime Anyspace AND/OR Best-First Search for Bounding Marginal MAP |
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3 |
| Approximate Inference via Weighted Rademacher Complexity |
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3 |
| Approximate Vanishing Ideal via Data Knotting |
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3 |
| Approximate and Exact Enumeration of Rule Models |
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3 |
| Approximately Stable Matchings With Budget Constraints |
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❌ |
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1 |
| Approximating Bribery in Scoring Rules |
✅ |
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❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Approximation-Variance Tradeoffs in Facility Location Games |
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❌ |
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0 |
| Argument Mining for Improving the Automated Scoring of Persuasive Essays |
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✅ |
✅ |
❌ |
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3 |
| Armstrong’s Axioms and Navigation Strategies |
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0 |
| Asking Friendly Strangers: Non-Semantic Attribute Transfer |
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3 |
| Assertion-Based QA With Question-Aware Open Information Extraction |
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❌ |
✅ |
✅ |
❌ |
❌ |
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2 |
| Asymmetric Action Abstractions for Multi-Unit Control in Adversarial Real-Time Games |
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❌ |
✅ |
❌ |
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3 |
| Asymmetric Deep Supervised Hashing |
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✅ |
✅ |
✅ |
❌ |
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5 |
| Asymmetric Joint Learning for Heterogeneous Face Recognition |
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✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Asynchronous Bidirectional Decoding for Neural Machine Translation |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
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5 |
| Asynchronous Doubly Stochastic Sparse Kernel Learning |
✅ |
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✅ |
❌ |
✅ |
❌ |
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4 |
| Attend and Diagnose: Clinical Time Series Analysis Using Attention Models |
✅ |
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✅ |
✅ |
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❌ |
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4 |
| Attention-Based Transactional Context Embedding for Next-Item Recommendation |
✅ |
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✅ |
✅ |
❌ |
❌ |
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4 |
| Attention-based Belief or Disbelief Feature Extraction for Dependency Parsing |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Attention-via-Attention Neural Machine Translation |
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❌ |
✅ |
✅ |
✅ |
❌ |
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4 |
| Audio Visual Attribute Discovery for Fine-Grained Object Recognition |
❌ |
❌ |
✅ |
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❌ |
❌ |
✅ |
3 |
| Augmenting End-to-End Dialogue Systems With Commonsense Knowledge |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Auto-Balanced Filter Pruning for Efficient Convolutional Neural Networks |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| AutoEncoder by Forest |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Automated Segmentation of Overlapping Cytoplasm in Cervical Smear Images via Contour Fragments |
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❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Automatic Generation of Text Descriptive Comments for Code Blocks |
❌ |
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✅ |
✅ |
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❌ |
✅ |
4 |
| Automatic Model Selection in Subspace Clustering via Triplet Relationships |
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✅ |
❌ |
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❌ |
❌ |
2 |
| Automatic Parameter Tying: A New Approach for Regularized Parameter Learning in Markov Networks |
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✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Automatic Segmentation of Data Sequences |
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❌ |
✅ |
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3 |
| Average-Case Approximation Ratio of Scheduling Without Payments |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Avoiding Dead Ends in Real-Time Heuristic Search |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
✅ |
3 |
| Axioms for Distance-Based Centralities |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Balanced Clustering via Exclusive Lasso: A Pragmatic Approach |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Batchwise Patching of Classifiers |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Bayesian Functional Optimization |
✅ |
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✅ |
4 |
| Bayesian Robust Attributed Graph Clustering: Joint Learning of Partial Anomalies and Group Structure |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Bayesian Verb Sense Clustering |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Behavior Is Everything: Towards Representing Concepts with Sensorimotor Contingencies |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Belief Reward Shaping in Reinforcement Learning |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Bernoulli Embeddings for Graphs |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Beyond Distributive Fairness in Algorithmic Decision Making: Feature Selection for Procedurally Fair Learning |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Beyond Link Prediction: Predicting Hyperlinks in Adjacency Space |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Beyond Sparsity: Tree Regularization of Deep Models for Interpretability |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Binary Generative Adversarial Networks for Image Retrieval |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Boosted Generative Models |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Brute-Force Facial Landmark Analysis With a 140,000-Way Classifier |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Budget-Constrained Multi-Armed Bandits With Multiple Plays |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Building Continuous Occupancy Maps With Moving Robots |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Building Deep Networks on Grassmann Manifolds |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Byte-Level Machine Reading Across Morphologically Varied Languages |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| CA-RNN: Using Context-Aligned Recurrent Neural Networks for Modeling Sentence Similarity |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| CD-CNN: A Partially Supervised Cross-Domain Deep Learning Model for Urban Resident Recognition |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| CMCGAN: A Uniform Framework for Cross-Modal Visual-Audio Mutual Generation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| COSINE: Community-Preserving Social Network Embedding From Information Diffusion Cascades |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| CSWA: Aggregation-Free Spatial-Temporal Community Sensing |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Canonical Correlation Inference for Mapping Abstract Scenes to Text |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Cascade and Parallel Convolutional Recurrent Neural Networks on EEG-based Intention Recognition for Brain Computer Interface |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Catching Captain Jack: Efficient Time and Space Dependent Patrols to Combat Oil-Siphoning in International Waters |
✅ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
4 |
| Cellular Network Traffic Scheduling With Deep Reinforcement Learning |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| Char-Net: A Character-Aware Neural Network for Distorted Scene Text Recognition |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Characterization of the Convex Łukasiewicz Fragment for Learning From Constraints |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Chinese LIWC Lexicon Expansion via Hierarchical Classification of Word Embeddings with Sememe Attention |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Classical Planning in Deep Latent Space: Bridging the Subsymbolic-Symbolic Boundary |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Clustering Small Samples With Quality Guarantees: Adaptivity With One2all PPS |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Co-Attending Free-Form Regions and Detections With Multi-Modal Multiplicative Feature Embedding for Visual Question Answering |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Co-Domain Embedding Using Deep Quadruplet Networks for Unseen Traffic Sign Recognition |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
4 |
| Co-Saliency Detection Within a Single Image |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| CoChat: Enabling Bot and Human Collaboration for Task Completion |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| CoDiNMF: Co-Clustering of Directed Graphs via NMF |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| CoLink: An Unsupervised Framework for User Identity Linkage |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Coalition Manipulation of Gale-Shapley Algorithm |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Cognition-Cognizant Sentiment Analysis With Multitask Subjectivity Summarization Based on Annotators’ Gaze Behavior |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Collaborative Filtering With Social Exposure: A Modular Approach to Social Recommendation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Collaborative Filtering With User-Item Co-Autoregressive Models |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
✅ |
6 |
| Combining Experts’ Causal Judgments |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Combining Rules and Ontologies into Clopen Knowledge Bases |
❌ |
❌ |
✅ |
❌ |
✅ |
✅ |
❌ |
3 |
| Committee Selection with Intraclass and Interclass Synergies |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Community Detection in Attributed Graphs: An Embedding Approach |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Community-Based Trip Sharing for Urban Commuting |
✅ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
4 |
| Compact Multi-Label Learning |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Comparing Population Means Under Local Differential Privacy: With Significance and Power |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Compatibility Family Learning for Item Recommendation and Generation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Complex Sequential Question Answering: Towards Learning to Converse Over Linked Question Answer Pairs with a Knowledge Graph |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Complexity of Verification in Incomplete Argumentation Frameworks |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Compressed Sensing MRI Using a Recursive Dilated Network |
❌ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
2 |
| Computation Error Analysis of Block Floating Point Arithmetic Oriented Convolution Neural Network Accelerator Design |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Computational Results for Extensive-Form Adversarial Team Games |
✅ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
4 |
| Computing the Strategy to Commit to in Polymatrix Games |
✅ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
4 |
| Conditional PSDDs: Modeling and Learning With Modular Knowledge |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Confidence-Aware Matrix Factorization for Recommender Systems |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Consistent and Specific Multi-View Subspace Clustering |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Constructive Preference Elicitation Over Hybrid Combinatorial Spaces |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Content and Context: Two-Pronged Bootstrapped Learning for Regex-Formatted Entity Extraction |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Context Aware Conversational Understanding for Intelligent Agents With a Screen |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Context-Aware Symptom Checking for Disease Diagnosis Using Hierarchical Reinforcement Learning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Contrastive Training for Models of Information Cascades |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Control Argumentation Frameworks |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Controlling Global Statistics in Recurrent Neural Network Text Generation |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Conversational Model Adaptation via KL Divergence Regularization |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Convolutional 2D Knowledge Graph Embeddings |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Cooperative Games With Bounded Dependency Degree |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Cooperative Learning of Energy-Based Model and Latent Variable Model via MCMC Teaching |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Cooperative Training of Deep Aggregation Networks for RGB-D Action Recognition |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Core Dependency Networks |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
4 |
| Counterfactual Multi-Agent Policy Gradients |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Counting Linear Extensions in Practice: MCMC Versus Exponential Monte Carlo |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Coupled Deep Learning for Heterogeneous Face Recognition |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Coupled Poisson Factorization Integrated With User/Item Metadata for Modeling Popular and Sparse Ratings in Scalable Recommendation |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Cross Temporal Recurrent Networks for Ranking Question Answer Pairs |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Cross-Domain Human Parsing via Adversarial Feature and Label Adaptation |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Cross-Lingual Entity Linking for Web Tables |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Cross-Lingual Propagation for Deep Sentiment Analysis |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Cross-View Person Identification by Matching Human Poses Estimated With Confidence on Each Body Joint |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Curve-Structure Segmentation From Depth Maps: A CNN-Based Approach and Its Application to Exploring Cultural Heritage Objects |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Customized Nonlinear Bandits for Online Response Selection in Neural Conversation Models |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| DF2Net: Discriminative Feature Learning and Fusion Network for RGB-D Indoor Scene Classification |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| DID: Distributed Incremental Block Coordinate Descent for Nonnegative Matrix Factorization |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| DLPaper2Code: Auto-Generation of Code From Deep Learning Research Papers |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| DarkRank: Accelerating Deep Metric Learning via Cross Sample Similarities Transfer |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Data Poisoning Attacks on Multi-Task Relationship Learning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Data-Dependent Learning of Symmetric/Antisymmetric Relations for Knowledge Base Completion |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Decentralised Learning in Systems With Many, Many Strategic Agents |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Decentralized High-Dimensional Bayesian Optimization With Factor Graphs |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Deception Detection in Videos |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Decomposition Strategies for Constructive Preference Elicitation |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
✅ |
4 |
| Deconvolutional Latent-Variable Model for Text Sequence Matching |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Decoupled Convolutions for CNNs |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Deep Asymmetric Transfer Network for Unbalanced Domain Adaptation |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Deep Learning for Case-Based Reasoning Through Prototypes: A Neural Network That Explains Its Predictions |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Deep Learning from Crowds |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Deep Low-Resolution Person Re-Identification |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction |
✅ |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
4 |
| Deep Neural Network Compression With Single and Multiple Level Quantization |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Deep Q-learning From Demonstrations |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Deep Region Hashing for Generic Instance Search from Images |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Deep Reinforcement Learning That Matters |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Deep Reinforcement Learning for Unsupervised Video Summarization With Diversity-Representativeness Reward |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Deep Representation-Decoupling Neural Networks for Monaural Music Mixture Separation |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Deep Semantic Role Labeling With Self-Attention |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Deep Semantic Structural Constraints for Zero-Shot Learning |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Deep Semi-Random Features for Nonlinear Function Approximation |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Deep Stereo Matching With Explicit Cost Aggregation Sub-Architecture |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Deep Structured Learning for Visual Relationship Detection |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Deep-Treat: Learning Optimal Personalized Treatments From Observational Data Using Neural Networks |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| DeepHeart: Semi-Supervised Sequence Learning for Cardiovascular Risk Prediction |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| DeepHit: A Deep Learning Approach to Survival Analysis With Competing Risks |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| DeepRebirth: Accelerating Deep Neural Network Execution on Mobile Devices |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| DeepType: Multilingual Entity Linking by Neural Type System Evolution |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| DeepUrbanMomentum: An Online Deep-Learning System for Short-Term Urban Mobility Prediction |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
5 |
| Dependence Guided Unsupervised Feature Selection |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Dependence in Propositional Logic: Formula-Formula Dependence and Formula Forgetting – Application to Belief Update and Conservative Extension |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| DepthLGP: Learning Embeddings of Out-of-Sample Nodes in Dynamic Networks |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Detecting Adversarial Examples Through Image Transformation |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Deterministic Policy Optimization by Combining Pathwise and Score Function Estimators for Discrete Action Spaces |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Diagnosing and Improving Topic Models by Analyzing Posterior Variability |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Dialogue Act Sequence Labeling Using Hierarchical Encoder With CRF |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Dictionary Learning Inspired Deep Network for Scene Recognition |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Dictionary Learning in Optimal Metric Space |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Differential Performance Debugging With Discriminant Regression Trees |
✅ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| Dilated FCN for Multi-Agent 2D/3D Medical Image Registration |
❌ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
2 |
| Direct Hashing Without Pseudo-Labels |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Directional Label Rectification in Adaptive Graph |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Disarmament Games With Resource |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Discovering and Distinguishing Multiple Visual Senses for Polysemous Words |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Discriminant Projection Representation-Based Classification for Vision Recognition |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Discriminative Semi-Coupled Projective Dictionary Learning for Low-Resolution Person Re-Identification |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Disjunctive Program Synthesis: A Robust Approach to Programming by Example |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Dispatch Guided Allocation Optimization for Effective Emergency Response |
✅ |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
4 |
| Distance-Aware DAG Embedding for Proximity Search on Heterogeneous Graphs |
✅ |
✅ |
✅ |
✅ |
✅ |
✅ |
✅ |
7 |
| Distant-Supervision of Heterogeneous Multitask Learning for Social Event Forecasting With Multilingual Indicators |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Distributed Composite Quantization |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Distributional Reinforcement Learning With Quantile Regression |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Diverse Beam Search for Improved Description of Complex Scenes |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Diverse Exploration for Fast and Safe Policy Improvement |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Does William Shakespeare REALLY Write Hamlet? Knowledge Representation Learning With Confidence |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Doing the Best We Can With What We Have: Multi-Label Balancing With Selective Learning for Attribute Prediction |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Domain Generalization via Conditional Invariant Representations |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Domain-Shared Group-Sparse Dictionary Learning for Unsupervised Domain Adaptation |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Double Forward Propagation for Memorized Batch Normalization |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Doubly Approximate Nearest Neighbor Classification |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Dress Fashionably: Learn Fashion Collocation With Deep Mixed-Category Metric Learning |
❌ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
2 |
| Dual Attention Network for Product Compatibility and Function Satisfiability Analysis |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Dual Deep Neural Networks Cross-Modal Hashing |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Dual Set Multi-Label Learning |
✅ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Dual-Reference Face Retrieval |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Duplicate Question Identification by Integrating FrameNet With Neural Networks |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| DyETC: Dynamic Electronic Toll Collection for Traffic Congestion Alleviation |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Dynamic Deep Neural Networks: Optimizing Accuracy-Efficiency Trade-Offs by Selective Execution |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Dynamic Determinantal Point Processes |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Dynamic Network Embedding by Modeling Triadic Closure Process |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Dynamic Optimization of Neural Network Structures Using Probabilistic Modeling |
✅ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
6 |
| Dynamic Pricing for Reusable Resources in Competitive Market With Stochastic Demand |
✅ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
4 |
| Dynamic User Profiling for Streams of Short Texts |
✅ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| EMD Metric Learning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Early Detection of Fake News on Social Media Through Propagation Path Classification with Recurrent and Convolutional Networks |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Early Prediction of Diabetes Complications from Electronic Health Records: A Multi-Task Survival Analysis Approach |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Early Syntactic Bootstrapping in an Incremental Memory-Limited Word Learner |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Effective Broad-Coverage Deep Parsing |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Effective Heuristics for Committee Scoring Rules |
❌ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
2 |
| Efficient Architecture Search by Network Transformation |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Efficient K-Shot Learning With Regularized Deep Networks |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Efficient Large-Scale Multi-Modal Classification |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Efficient Multi-Dimensional Tensor Sparse Coding Using t-Linear Combination |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Efficient Probabilistic Performance Bounds for Inverse Reinforcement Learning |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Efficient Test-Time Predictor Learning With Group-Based Budget |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Efficient-UCBV: An Almost Optimal Algorithm Using Variance Estimates |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Efficiently Approximating the Pareto Frontier: Hydropower Dam Placement in the Amazon Basin |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Efficiently Monitoring Small Data Modification Effect for Large-Scale Learning in Changing Environment |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Elastic Responding Machine for Dialog Generation with Dynamically Mechanism Selecting |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Eliciting Positive Emotion through Affect-Sensitive Dialogue Response Generation: A Neural Network Approach |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Embedding of Hierarchically Typed Knowledge Bases |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Emergence of Grounded Compositional Language in Multi-Agent Populations |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memory |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Emphasizing 3D Properties in Recurrent Multi-View Aggregation for 3D Shape Retrieval |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Empower Sequence Labeling with Task-Aware Neural Language Model |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| End-to-End Quantum-like Language Models with Application to Question Answering |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| End-to-End United Video Dehazing and Detection |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Energy-Efficient Automatic Train Driving by Learning Driving Patterns |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Enhancing Constraint-Based Multi-Objective Combinatorial Optimization |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
6 |
| Equilibrium Computation and Robust Optimization in Zero Sum Games With Submodular Structure |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Estimating the Class Prior in Positive and Unlabeled Data Through Decision Tree Induction |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Euler Sparse Representation for Image Classification |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Event Detection via Gated Multilingual Attention Mechanism |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| Event Representations With Tensor-Based Compositions |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Event Representations for Automated Story Generation with Deep Neural Nets |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
4 |
| Exact Clustering via Integer Programming and Maximum Satisfiability |
❌ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
4 |
| Exact MAP-Inference by Confining Combinatorial Search With LP Relaxation |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
✅ |
5 |
| Examining CNN Representations With Respect to Dataset Bias |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Exercise-Enhanced Sequential Modeling for Student Performance Prediction |
❌ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
2 |
| Expected Policy Gradients |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Expected Utility with Relative Loss Reduction: A Unifying Decision Model for Resolving Four Well-Known Paradoxes |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Explicit Reasoning over End-to-End Neural Architectures for Visual Question Answering |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| Exploiting Emotion on Reviews for Recommender Systems |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Exploring Human-Like Attention Supervision in Visual Question Answering |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Exploring Implicit Feedback for Open Domain Conversation Generation |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Exploring Temporal Preservation Networks for Precise Temporal Action Localization |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Exploring the Terrain of Metaphor Novelty: A Regression-Based Approach for Automatically Scoring Metaphors |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| ExprGAN: Facial Expression Editing With Controllable Expression Intensity |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Expressive Real-Time Intersection Scheduling |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Externally Supported Models for Efficient Computation of Paracoherent Answer Sets |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
2 |
| Extreme Low Resolution Activity Recognition With Multi-Siamese Embedding Learning |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
3 |
| Extremely Low Bit Neural Network: Squeeze the Last Bit Out With ADMM |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| FEEL: Featured Event Embedding Learning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| FILE: A Novel Framework for Predicting Social Status in Signed Networks |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| FLIC: Fast Linear Iterative Clustering With Active Search |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Face Sketch Synthesis From Coarse to Fine |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Facial Landmarks Detection by Self-Iterative Regression Based Landmarks-Attention Network |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Facility Location Games With Fractional Preferences |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Fact Checking in Community Forums |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| Fair Inference on Outcomes |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Fair Rent Division on a Budget |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Fairness in Decision-Making — The Causal Explanation Formula |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Faithful to the Original: Fact Aware Neural Abstractive Summarization |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Fat- and Heavy-Tailed Behavior in Satisficing Planning |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Feature Engineering for Predictive Modeling Using Reinforcement Learning |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Feature Enhancement Network: A Refined Scene Text Detector |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Feature-Induced Labeling Information Enrichment for Multi-Label Learning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Few Shot Transfer Learning BetweenWord Relatedness and Similarity Tasks Using A Gated Recurrent Siamese Network |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| FiLM: Visual Reasoning with a General Conditioning Layer |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Finite Sample Analyses for TD(0) With Function Approximation |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Forgetting and Unfolding for Existential Rules |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Fourier Feature Approximations for Periodic Kernels in Time-Series Modelling |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| From Common to Special: When Multi-Attribute Learning Meets Personalized Opinions |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| From Hashing to CNNs: Training Binary Weight Networks via Hashing |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| From Monte Carlo to Las Vegas: Improving Restricted Boltzmann Machine Training Through Stopping Sets |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| From Virtual Demonstration to Real-World Manipulation Using LSTM and MDN |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Fully Convolutional Network Based Skeletonization for Handwritten Chinese Characters |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Game of Sketches: Deep Recurrent Models of Pictionary-Style Word Guessing |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Gated-Attention Architectures for Task-Oriented Language Grounding |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Gaussian Process Decentralized Data Fusion Meets Transfer Learning in Large-Scale Distributed Cooperative Perception |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Generalized Adjustment Under Confounding and Selection Biases |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Generalized Value Iteration Networks:Life Beyond Lattices |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Generalizing and Improving Bilingual Word Embedding Mappings with a Multi-Step Framework of Linear Transformations |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Generating Music Medleys via Playing Music Puzzle Games |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Generating Sentences Using a Dynamic Canvas |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Generating Triples With Adversarial Networks for Scene Graph Construction |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Generating an Event Timeline About Daily Activities From a Semantic Concept Stream |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Generative Adversarial Network Based Heterogeneous Bibliographic Network Representation for Personalized Citation Recommendation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Geographic Differential Privacy for Mobile Crowd Coverage Maximization |
✅ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
6 |
| Geometric Relationship between Word and Context Representations |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Glass-Box Program Synthesis: A Machine Learning Approach |
✅ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| Goal-Driven Query Answering for Existential Rules With Equality |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Graph Convolutional Networks With Argument-Aware Pooling for Event Detection |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Graph Correspondence Transfer for Person Re-Identification |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Graph Scan Statistics With Uncertainty |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| GraphGAN: Graph Representation Learning With Generative Adversarial Nets |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Group Sparse Bayesian Learning for Active Surveillance on Epidemic Dynamics |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
4 |
| Group-Pair Convolutional Neural Networks for Multi-View Based 3D Object Retrieval |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Groupwise Maximin Fair Allocation of Indivisible Goods |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Guiding Exploratory Behaviors for Multi-Modal Grounding of Linguistic Descriptions |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Guiding Search in Continuous State-Action Spaces by Learning an Action Sampler From Off-Target Search Experience |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| HAN: Hierarchical Association Network for Computing Semantic Relatedness |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| HARP: Hierarchical Representation Learning for Networks |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| HCVRD: A Benchmark for Large-Scale Human-Centered Visual Relationship Detection |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Hawkes Process Inference With Missing Data |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Hierarchical Attention Flow for Multiple-Choice Reading Comprehension |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Hierarchical Attention Transfer Network for Cross-Domain Sentiment Classification |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Hierarchical Discriminative Learning for Visible Thermal Person Re-Identification |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Hierarchical LSTM for Sign Language Translation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Hierarchical Nonlinear Orthogonal Adaptive-Subspace Self-Organizing Map Based Feature Extraction for Human Action Recognition |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Hierarchical Policy Search via Return-Weighted Density Estimation |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Hierarchical Recurrent Attention Network for Response Generation |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Hierarchical Video Generation From Orthogonal Information: Optical Flow and Texture |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| High Rank Matrix Completion With Side Information |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| HodgeRank With Information Maximization for Crowdsourced Pairwise Ranking Aggregation |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| HogRider: Champion Agent of Microsoft Malmo Collaborative AI Challenge |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
3 |
| How AI Wins Friends and Influences People in Repeated Games With Cheap Talk |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| How Images Inspire Poems: Generating Classical Chinese Poetry from Images with Memory Networks |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| How Many Properties Do We Need for Gradual Argumentation? |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Human Guided Linear Regression With Feature-Level Constraints |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Human-in-the-Loop SLAM |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
❌ |
3 |
| Hybrid Attentive Answer Selection in CQA With Deep Users Modelling |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Hypergraph Learning With Cost Interval Optimization |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Hypergraph p-Laplacian: A Differential Geometry View |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| IMS-DTM: Incremental Multi-Scale Dynamic Topic Models |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| IONet: Learning to Cure the Curse of Drift in Inertial Odometry |
❌ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
2 |
| Imitation Learning via Kernel Mean Embedding |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Improved English to Russian Translation by Neural Suffix Prediction |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Improved Results for Minimum Constraint Removal |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Improved Text Matching by Enhancing Mutual Information |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Improving Language Modelling with Noise Contrastive Estimation |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Improving Neural Fine-Grained Entity Typing With Knowledge Attention |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Improving Review Representations With User Attention and Product Attention for Sentiment Classification |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Improving Sequence-to-Sequence Constituency Parsing |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Improving Variational Encoder-Decoders in Dialogue Generation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing Their Input Gradients |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| In Praise of Belief Bases: Doing Epistemic Logic Without Possible Worlds |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Incentive-Compatible Forecasting Competitions |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Incentivizing High Quality User Contributions: New Arm Generation in Bandit Learning |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Incomplete Label Multi-Task Ordinal Regression for Spatial Event Scale Forecasting |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Incorporating Discriminator in Sentence Generation: a Gibbs Sampling Method |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Incorporating GAN for Negative Sampling in Knowledge Representation Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Inexact Proximal Gradient Methods for Non-Convex and Non-Smooth Optimization |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Inference on Syntactic and Semantic Structures for Machine Comprehension |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Inferring Emotion from Conversational Voice Data: A Semi-Supervised Multi-Path Generative Neural Network Approach |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| Information Acquisition Under Resource Limitations in a Noisy Environment |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Information Directed Sampling for Stochastic Bandits With Graph Feedback |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Information Gathering With Peers: Submodular Optimization With Peer-Prediction Constraints |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Information-Theoretic Domain Adaptation Under Severe Noise Conditions |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Informed Non-Convex Robust Principal Component Analysis With Features |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Integrated Cooperation and Competition in Multi-Agent Decision-Making |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Integrating Both Visual and Audio Cues for Enhanced Video Caption |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Interactively Learning a Blend of Goal-Based and Procedural Tasks |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Interpretable Graph-Based Semi-Supervised Learning via Flows |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Interpreting CNN Knowledge via an Explanatory Graph |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Investigating Inner Properties of Multimodal Representation and Semantic Compositionality With Brain-Based Componential Semantics |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| It Takes (Only) Two: Adversarial Generator-Encoder Networks |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Iterative Continuous Convolution for 3D Template Matching and Global Localization |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| Joint Dictionaries for Zero-Shot Learning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| Joint Learning of Set Cardinality and State Distribution |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Joint Training for Neural Machine Translation Models with Monolingual Data |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Jointly Extracting Event Triggers and Arguments by Dependency-Bridge RNN and Tensor-Based Argument Interaction |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Jointly Parse and Fragment Ungrammatical Sentences |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Kernel Cross-Correlator |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Kill Two Birds With One Stone: Weakly-Supervised Neural Network for Image Annotation and Tag Refinement |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Knowledge Enhanced Hybrid Neural Network for Text Matching |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Knowledge Graph Embedding With Iterative Guidance From Soft Rules |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Knowledge, Fairness, and Social Constraints |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Knowledge-Based Policies for Qualitative Decentralized POMDPs |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Knowledge-based Word Sense Disambiguation using Topic Models |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| LSTD: A Low-Shot Transfer Detector for Object Detection |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| LTLf/LDLf Non-Markovian Rewards |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Label Distribution Learning by Exploiting Label Correlations |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Label Distribution Learning by Exploiting Sample Correlations Locally |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Label Distribution Learning by Optimal Transport |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Labeled Memory Networks for Online Model Adaptation |
✅ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
6 |
| Lagrangian Constrained Community Detection |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Large Scale Constrained Linear Regression Revisited: Faster Algorithms via Preconditioning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Large Scaled Relation Extraction With Reinforcement Learning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Latent Discriminant Subspace Representations for Multi-View Outlier Detection |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Latent Semantic Aware Multi-View Multi-Label Classification |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Latent Sparse Modeling of Longitudinal Multi-Dimensional Data |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Lateral Inhibition-Inspired Convolutional Neural Network for Visual Attention and Saliency Detection |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Lattice Recurrent Unit: Improving Convergence and Statistical Efficiency for Sequence Modeling |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Leaf-Smoothed Hierarchical Softmax for Ordinal Prediction |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning Abduction Using Partial Observability |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Learning Across Scales—Multiscale Methods for Convolution Neural Networks |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning Adaptive Hidden Layers for Mobile Gesture Recognition |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning Adversarial 3D Model Generation With 2D Image Enhancer |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Learning Better Name Translation for Cross-Lingual Wikification |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Learning Binary Residual Representations for Domain-Specific Video Streaming |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Learning Coarse-to-Fine Structured Feature Embedding for Vehicle Re-Identification |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Learning Combinatory Categorial Grammars for Plan Recognition |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning Conditional Generative Models for Temporal Point Processes |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Learning Datum-Wise Sampling Frequency for Energy-Efficient Human Activity Recognition |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning Differences Between Visual Scanning Patterns Can Disambiguate Bipolar and Unipolar Patients |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Learning From Semi-Supervised Weak-Label Data |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning From Unannotated QA Pairs to Analogically Disambiguate and Answer Questions |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| Learning Generative Neural Networks for 3D Colorization |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Learning Graph-Structured Sum-Product Networks for Probabilistic Semantic Maps |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Learning Integrated Holism-Landmark Representations for Long-Term Loop Closure Detection |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Learning Interpretable Spatial Operations in a Rich 3D Blocks World |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning Latent Opinions for Aspect-level Sentiment Classification |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning Lexicographic Preference Trees From Positive Examples |
✅ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
6 |
| Learning Mixtures of MLNs |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning Mixtures of Random Utility Models |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
3 |
| Learning Multi-Modal Word Representation Grounded in Visual Context |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning Multi-Way Relations via Tensor Decomposition With Neural Networks |
✅ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
6 |
| Learning Multimodal Word Representation via Dynamic Fusion Methods |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning Nonlinear Dynamics in Efficient, Balanced Spiking Networks Using Local Plasticity Rules |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Learning Pose Grammar to Encode Human Body Configuration for 3D Pose Estimation |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Learning Predictive State Representations From Non-Uniform Sampling |
✅ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning Robust Options |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Learning Robust Search Strategies Using a Bandit-Based Approach |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Learning Sentiment-Specific Word Embedding via Global Sentiment Representation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning Spatio-Temporal Features With Partial Expression Sequences for On-the-Fly Prediction |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning Structured Representation for Text Classification via Reinforcement Learning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Learning Transferable Subspace for Human Motion Segmentation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Learning User Preferences to Incentivize Exploration in the Sharing Economy |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Learning Vector Autoregressive Models With Latent Processes |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Learning With Incomplete Labels |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| Learning With Options That Terminate Off-Policy |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Learning With Single-Teacher Multi-Student |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning a Wavelet-Like Auto-Encoder to Accelerate Deep Neural Networks |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Learning the Behavior of a Dynamical System Via a “20 Questions” Approach |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Learning the Joint Representation of Heterogeneous Temporal Events for Clinical Endpoint Prediction |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning the Probability of Activation in the Presence of Latent Spreaders |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Learning to Attack: Adversarial Transformation Networks |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning to Attend via Word-Aspect Associative Fusion for Aspect-Based Sentiment Analysis |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Learning to Compose Task-Specific Tree Structures |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Learning to Extract Coherent Summary via Deep Reinforcement Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning to Generalize: Meta-Learning for Domain Generalization |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Learning to Guide Decoding for Image Captioning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning to Interact With Learning Agents |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Learning to Predict Readability Using Eye-Movement Data From Natives and Learners |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Learning to Rank Based on Analogical Reasoning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Less-Forgetful Learning for Domain Expansion in Deep Neural Networks |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Leveraging Lexical Substitutes for Unsupervised Word Sense Induction |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Lifted Generalized Dual Decomposition |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Linear and Integer Programming-Based Heuristics for Cost-Optimal Numeric Planning |
❌ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
4 |
| Linguistic Properties Matter for Implicit Discourse Relation Recognition: Combining Semantic Interaction, Topic Continuity and Attribution |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Link Prediction With Personalized Social Influence |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Link Prediction via Subgraph Embedding-Based Convex Matrix Completion |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Liquid Democracy: An Algorithmic Perspective |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Listening to the World Improves Speech Command Recognition |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Load Scheduling of Simple Temporal Networks Under Dynamic Resource Pricing |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Locality Preserving Projection Based on F-norm |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| Location-Sensitive User Profiling Using Crowdsourced Labels |
✅ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| Long Text Generation via Adversarial Training with Leaked Information |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Long-Term Image Boundary Prediction |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| MDP-Based Cost Sensitive Classification Using Decision Trees |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| MERCS: Multi-Directional Ensembles of Regression and Classification Trees |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| MUDA: A Truthful Multi-Unit Double-Auction Mechanism |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Machine-Translated Knowledge Transfer for Commonsense Causal Reasoning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| Manipulative Elicitation — A New Attack on Elections with Incomplete Preferences |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Margin Based PU Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| MathDQN: Solving Arithmetic Word Problems via Deep Reinforcement Learning |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Matrix Variate Gaussian Mixture Distribution Steered Robust Metric Learning |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| MaxSAT Resolution With the Dual Rail Encoding |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
✅ |
2 |
| Maximizing Activity in Ising Networks via the TAP Approximation |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Maximizing Influence in an Unknown Social Network |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Maximum A Posteriori Inference in Sum-Product Networks |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Maximum-Variance Total Variation Denoising for Interpretable Spatial Smoothing |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Measuring Catastrophic Forgetting in Neural Networks |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Measuring Conditional Independence by Independent Residuals: Theoretical Results and Application in Causal Discovery |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Measuring Strong Inconsistency |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Measuring the Popularity of Job Skills in Recruitment Market: A Multi-Criteria Approach |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Medical Exam Question Answering with Large-scale Reading Comprehension |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Memory Fusion Network for Multi-view Sequential Learning |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
4 |
| Memory-Augmented Monte Carlo Tree Search |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Mention and Entity Description Co-Attention for Entity Disambiguation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Merge or Not? Learning to Group Faces via Imitation Learning |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Mesh-Based Autoencoders for Localized Deformation Component Analysis |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Meta Multi-Task Learning for Sequence Modeling |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Meta-Search Through the Space of Representations and Heuristics on a Problem by Problem Basis |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Metric-Based Auto-Instructor for Learning Mixed Data Representation |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Minesweeper with Limited Moves |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Mining Heavy Temporal Subgraphs: Fast Algorithms and Applications |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Mitigating Overexposure in Viral Marketing |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Mix-and-Match Tuning for Self-Supervised Semantic Segmentation |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| MixedPeds: Pedestrian Detection in Unannotated Videos Using Synthetically Generated Human-Agents for Training |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Model-Free Iterative Temporal Appliance Discovery for Unsupervised Electricity Disaggregation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Modeling Attention and Memory for Auditory Selection in a Cocktail Party Environment |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Modeling Scientific Influence for Research Trending Topic Prediction |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Modeling Temporal Tonal Relations in Polyphonic Music Through Deep Networks With a Novel Image-Based Representation |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Modelling Iterative Judgment Aggregation |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Movie Question Answering: Remembering the Textual Cues for Layered Visual Contents |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Multi-Adversarial Domain Adaptation |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Multi-Channel Encoder for Neural Machine Translation |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Multi-Channel Pyramid Person Matching Network for Person Re-Identification |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Multi-Entity Aspect-Based Sentiment Analysis With Context, Entity and Aspect Memory |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Multi-Entity Dependence Learning With Rich Context via Conditional Variational Auto-Encoder |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Multi-Facet Network Embedding: Beyond the General Solution of Detection and Representation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Multi-Layer Multi-View Classification for Alzheimer’s Disease Diagnosis |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Multi-Level Variational Autoencoder: Learning Disentangled Representations From Grouped Observations |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Multi-Modal Multi-Task Learning for Automatic Dietary Assessment |
❌ |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
3 |
| Multi-Rate Gated Recurrent Convolutional Networks for Video-Based Pedestrian Re-Identification |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Multi-Scale Bidirectional FCN for Object Skeleton Extraction |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Multi-Scale Face Restoration With Sequential Gating Ensemble Network |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Multi-Step Reinforcement Learning: A Unifying Algorithm |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Multi-Step Time Series Generator for Molecular Dynamics |
❌ |
❌ |
❌ |
❌ |
✅ |
✅ |
❌ |
2 |
| Multi-Task Learning For Parsing The Alexa Meaning Representation Language |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Multi-Task Medical Concept Normalization Using Multi-View Convolutional Neural Network |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Multi-View Multi-Graph Embedding for Brain Network Clustering Analysis |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Multi-attention Recurrent Network for Human Communication Comprehension |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
4 |
| Multiagent Connected Path Planning: PSPACE-Completeness and How to Deal With It |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Multiagent Simple Temporal Problem: The Arc-Consistency Approach |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Multimodal Keyless Attention Fusion for Video Classification |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Multimodal Poisson Gamma Belief Network |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Multispectral Transfer Network: Unsupervised Depth Estimation for All-Day Vision |
❌ |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
3 |
| Multiwinner Elections With Diversity Constraints |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and Accompaniment |
❌ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Neural Character-level Dependency Parsing for Chinese |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Neural Cross-Lingual Entity Linking |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Neural Ideal Point Estimation Network |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| Neural Knowledge Acquisition via Mutual Attention Between Knowledge Graph and Text |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Neural Link Prediction over Aligned Networks |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Neural Machine Translation with Gumbel-Greedy Decoding |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Neural Networks Incorporating Dictionaries for Chinese Word Segmentation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Neural Response Generation With Dynamic Vocabularies |
✅ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
6 |
| Never Retreat, Never Retract: Argumentation Analysis for Political Speeches |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| New l2,1-Norm Relaxation of Multi-Way Graph Cut for Clustering |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| No Modes Left Behind: Capturing the Data Distribution Effectively Using GANs |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Noisy Derivative-Free Optimization With Value Suppression |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Non-Discriminatory Machine Learning Through Convex Fairness Criteria |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Non-Exploitable Protocols for Repeated Cake Cutting |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Non-Parametric Outliers Detection in Multiple Time Series A Case Study: Power Grid Data Analysis |
✅ |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
4 |
| Nonconvex Sparse Spectral Clustering by Alternating Direction Method of Multipliers and Its Convergence Analysis |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Nonlinear Pairwise Layer and Its Training for Kernel Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Nonlocal Patch Based t-SVD for Image Inpainting: Algorithm and Error Analysis |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Nonparametric Stochastic Contextual Bandits |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Norm Conflict Resolution in Stochastic Domains |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| OTyper: A Neural Architecture for Open Named Entity Typing |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| On Consensus in Belief Merging |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| On Controlling the Size of Clusters in Probabilistic Clustering |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| On Convergence of Epanechnikov Mean Shift |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| On Cryptographic Attacks Using Backdoors for SAT |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
3 |
| On Data-Dependent Random Features for Improved Generalization in Supervised Learning |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| On Multi-Relational Link Prediction With Bilinear Models |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| On Multiset Selection With Size Constraints |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| On Organizing Online Soirees with Live Multi-Streaming |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
3 |
| On Recognising Nearly Single-Crossing Preferences |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| On Social Envy-Freeness in Multi-Unit Markets |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| On Trivial Solution and High Correlation Problems in Deep Supervised Hashing |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| On Validation and Predictability of Digital Badges’ Influence on Individual Users |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| On Value Function Representation of Long Horizon Problems |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| On the Approximation of Nash Equilibria in Sparse Win-Lose Games |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| On the Complexity of Extended and Proportional Justified Representation |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| On the Distortion of Voting With Multiple Representative Candidates |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| On the ERM Principle With Networked Data |
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1 |
| On the Optimal Bit Complexity of Circulant Binary Embedding |
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1 |
| On the Relationship Between State-Dependent Action Costs and Conditional Effects in Planning |
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✅ |
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1 |
| On the Satisfiability Problem of Patterns in SPARQL 1.1 |
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❌ |
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0 |
| On the Time and Space Complexity of Genetic Programming for Evolving Boolean Conjunctions |
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1 |
| Online Clustering of Contextual Cascading Bandits |
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3 |
| Online Learning for Structured Loss Spaces |
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1 |
| Open-World Knowledge Graph Completion |
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4 |
| Optimal Approximation of Random Variables for Estimating the Probability of Meeting a Plan Deadline |
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4 |
| Optimal Margin Distribution Clustering |
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5 |
| Optimal Spot-Checking for Improving Evaluation Accuracy of Peer Grading Systems |
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4 |
| Optimised Maintenance of Datalog Materialisations |
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❌ |
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❌ |
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5 |
| Optimizing Interventions via Offline Policy Evaluation: Studies in Citizen Science |
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✅ |
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❌ |
✅ |
5 |
| OptionGAN: Learning Joint Reward-Policy Options Using Generative Adversarial Inverse Reinforcement Learning |
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❌ |
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❌ |
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4 |
| Order-Free RNN With Visual Attention for Multi-Label Classification |
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3 |
| Order-Planning Neural Text Generation From Structured Data |
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❌ |
❌ |
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4 |
| Orthant-Wise Passive Descent Algorithms for Training L1-Regularized Models |
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❌ |
✅ |
3 |
| Orthogonal Weight Normalization: Solution to Optimization Over Multiple Dependent Stiefel Manifolds in Deep Neural Networks |
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✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Overlap-Robust Decision Boundary Learning for Within-Network Classification |
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✅ |
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❌ |
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✅ |
5 |
| PAC Reinforcement Learning With an Imperfect Model |
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1 |
| POMDP-Based Decision Making for Fast Event Handling in VANETs |
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❌ |
✅ |
✅ |
3 |
| PVL: A Framework for Navigating the Precision-Variety Trade-Off in Automated Animation of Smiles |
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❌ |
✅ |
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❌ |
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4 |
| Parallel Algorithms for Operations on Multi-Valued Decision Diagrams |
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2 |
| Parameter-Free Centralized Multi-Task Learning for Characterizing Developmental Sex Differences in Resting State Functional Connectivity |
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4 |
| Partial Multi-Label Learning |
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3 |
| Partial Multi-View Outlier Detection Based on Collective Learning |
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3 |
| Partial Truthfulness in Minimal Peer Prediction Mechanisms With Limited Knowledge |
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1 |
| Perceiving, Learning, and Recognizing 3D Objects: An Approach to Cognitive Service Robots |
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2 |
| Perception Coordination Network: A Framework for Online Multi-Modal Concept Acquisition and Binding |
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3 |
| Personalized Privacy-Preserving Social Recommendation |
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❌ |
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5 |
| Personalized Time-Aware Tag Recommendation |
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3 |
| Personalizing a Dialogue System With Transfer Reinforcement Learning |
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2 |
| Persuasive Influence Detection: The Role of Argument Sequencing |
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3 |
| Phase-Parametric Policies for Reinforcement Learning in Cyclic Environments |
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1 |
| Picasso, Matisse, or a Fake? Automated Analysis of Drawings at the Stroke Level for Attribution and Authentication |
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2 |
| PixelLink: Detecting Scene Text via Instance Segmentation |
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4 |
| Placing Objects in Gesture Space: Toward Incremental Interpretation of Multimodal Spatial Descriptions |
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2 |
| Plan Recognition in Continuous Domains |
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2 |
| Planning With Pixels in (Almost) Real Time |
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4 |
| Planning and Learning for Decentralized MDPs With Event Driven Rewards |
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2 |
| Policy Learning for Continuous Space Security Games Using Neural Networks |
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2 |
| PoseHD: Boosting Human Detectors Using Human Pose Information |
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3 |
| Preallocation and Planning Under Stochastic Resource Constraints |
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2 |
| Predicting Aesthetic Score Distribution Through Cumulative Jensen-Shannon Divergence |
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3 |
| Predicting Links in Plant-Pollinator Interaction Networks Using Latent Factor Models With Implicit Feedback |
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3 |
| Predicting Vehicular Travel Times by Modeling Heterogeneous Influences Between Arterial Roads |
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3 |
| Predictive Coding Machine for Compressed Sensing and Image Denoising |
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4 |
| Premise Set Caching for Enumerating Minimal Correction Subsets |
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5 |
| Preventing Infectious Disease in Dynamic Populations Under Uncertainty |
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3 |
| Privacy Preserving Point-of-Interest Recommendation Using Decentralized Matrix Factorization |
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2 |
| Privacy-Preserving Policy Iteration for Decentralized POMDPs |
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3 |
| Probabilistic Ensemble of Collaborative Filters |
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4 |
| Probabilistic Inference Over Repeated Insertion Models |
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4 |
| Product Quantized Translation for Fast Nearest Neighbor Search |
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5 |
| Progressive Cognitive Human Parsing |
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3 |
| Proper Loss Functions for Nonlinear Hawkes Processes |
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4 |
| Proximal Alternating Direction Network: A Globally Converged Deep Unrolling Framework |
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4 |
| Qualitative Reasoning About Cardinal Directions Using Answer Set Programming |
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2 |
| Quantized Memory-Augmented Neural Networks |
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2 |
| Question Answering as Global Reasoning Over Semantic Abstractions |
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2 |
| Question-Answering with Grammatically-Interpretable Representations |
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❌ |
✅ |
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4 |
| R-FCN++: Towards Accurate Region-Based Fully Convolutional Networks for Object Detection |
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❌ |
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4 |
| R3: Reinforced Ranker-Reader for Open-Domain Question Answering |
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4 |
| RAN4IQA: Restorative Adversarial Nets for No-Reference Image Quality Assessment |
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❌ |
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4 |
| RNN-Based Sequence-Preserved Attention for Dependency Parsing |
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5 |
| ROAR: Robust Label Ranking for Social Emotion Mining |
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4 |
| RSDNE: Exploring Relaxed Similarity and Dissimilarity from Completely-Imbalanced Labels for Network Embedding |
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3 |
| RUBER: An Unsupervised Method for Automatic Evaluation of Open-Domain Dialog Systems |
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1 |
| Rainbow: Combining Improvements in Deep Reinforcement Learning |
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2 |
| Randomized Clustered Nystrom for Large-Scale Kernel Machines |
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4 |
| Randomized Kernel Selection With Spectra of Multilevel Circulant Matrices |
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2 |
| Rank Maximal Equal Contribution: A Probabilistic Social Choice Function |
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1 |
| Ranking Users in Social Networks With Higher-Order Structures |
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3 |
| Ranking Wily People Who Rank Each Other |
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3 |
| Rational Inference Patterns Based on Conditional Logic |
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1 |
| Recognizing and Justifying Text Entailment Through Distributional Navigation on Definition Graphs |
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2 |
| Recurrent Attentional Reinforcement Learning for Multi-Label Image Recognition |
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4 |
| Recurrently Aggregating Deep Features for Salient Object Detection |
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3 |
| Reduced-Rank Linear Dynamical Systems |
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6 |
| Region-Based Quality Estimation Network for Large-Scale Person Re-Identification |
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1 |
| Regularizing Deep Networks Using Efficient Layerwise Adversarial Training |
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4 |
| Reinforced Multi-Label Image Classification by Exploring Curriculum |
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5 |
| Reinforcement Learning for Relation Classification From Noisy Data |
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4 |
| Reinforcement Learning in POMDPs With Memoryless Options and Option-Observation Initiation Sets |
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1 |
| Reinforcement Mechanism Design for Fraudulent Behaviour in e-Commerce |
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3 |
| RelNN: A Deep Neural Model for Relational Learning |
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3 |
| Relational Marginal Problems: Theory and Estimation |
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0 |
| Reliable Multi-View Clustering |
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5 |
| Repairing Ontologies via Axiom Weakening |
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3 |
| Representation Learning for Scale-Free Networks |
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2 |
| Residual Encoder Decoder Network and Adaptive Prior for Face Parsing |
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3 |
| Resource Allocation Polytope Games: Uniqueness of Equilibrium, Price of Stability, and Price of Anarchy |
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1 |
| Resource-Constrained Scheduling for Maritime Traffic Management |
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3 |
| Retrieving and Classifying Affective Images via Deep Metric Learning |
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4 |
| Reversible Architectures for Arbitrarily Deep Residual Neural Networks |
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3 |
| Revisiting Immediate Duplicate Detection in External Memory Search |
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5 |
| Rich Coalitional Resource Games |
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1 |
| Riemannian Stein Variational Gradient Descent for Bayesian Inference |
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4 |
| Risk-Aware Proactive Scheduling via Conditional Value-at-Risk |
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4 |
| Risk-Sensitive Submodular Optimization |
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3 |
| Robust Collaborative Discriminative Learning for RGB-Infrared Tracking |
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3 |
| Robust Detection of Link Communities in Large Social Networks by Exploiting Link Semantics |
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3 |
| Robust Formulation for PCA: Avoiding Mean Calculation With L2,p-norm Maximization |
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2 |
| Robust Stackelberg Equilibria in Extensive-Form Games and Extension to Limited Lookahead |
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❌ |
✅ |
✅ |
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3 |
| Rocket Launching: A Universal and Efficient Framework for Training Well-Performing Light Net |
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4 |
| S-Net: From Answer Extraction to Answer Synthesis for Machine Reading Comprehension |
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3 |
| SAGA: A Submodular Greedy Algorithm for Group Recommendation |
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3 |
| SAP: Self-Adaptive Proposal Model for Temporal Action Detection Based on Reinforcement Learning |
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✅ |
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6 |
| SC2Net: Sparse LSTMs for Sparse Coding |
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4 |
| SEE: Syntax-Aware Entity Embedding for Neural Relation Extraction |
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❌ |
✅ |
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3 |
| SEE: Towards Semi-Supervised End-to-End Scene Text Recognition |
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✅ |
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4 |
| SELF: Structural Equational Likelihood Framework for Causal Discovery |
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✅ |
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3 |
| SFCN-OPI: Detection and Fine-Grained Classification of Nuclei Using Sibling FCN With Objectness Prior Interaction |
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4 |
| SNNN: Promoting Word Sentiment and Negation in Neural Sentiment Classification |
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✅ |
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2 |
| SPINE: SParse Interpretable Neural Embeddings |
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4 |
| Safe Exploration and Optimization of Constrained MDPs Using Gaussian Processes |
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3 |
| Safe Reinforcement Learning via Formal Methods: Toward Safe Control Through Proof and Learning |
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✅ |
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4 |
| Safe Reinforcement Learning via Shielding |
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3 |
| Sample-Efficient Learning of Mixtures |
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1 |
| Scalable Relaxations of Sparse Packing Constraints: Optimal Biocontrol in Predator-Prey Networks |
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4 |
| Scale Up Event Extraction Learning via Automatic Training Data Generation |
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3 |
| Scene-Centric Joint Parsing of Cross-View Videos |
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1 |
| Scheduling in Visual Fog Computing: NP-Completeness and Practical Efficient Solutions |
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✅ |
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1 |
| Schur Number Five |
❌ |
✅ |
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❌ |
✅ |
✅ |
✅ |
4 |
| SciTaiL: A Textual Entailment Dataset from Science Question Answering |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Search Action Sequence Modeling With Long Short-Term Memory for Search Task Success Evaluation |
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❌ |
✅ |
✅ |
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❌ |
✅ |
3 |
| Search Engine Guided Neural Machine Translation |
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✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Selective Experience Replay for Lifelong Learning |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Selective Verification Strategy for Learning From Crowds |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Self-Reinforced Cascaded Regression for Face Alignment |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| Self-View Grounding Given a Narrated 360° Video |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Semantic Structure-Based Word Embedding by Incorporating Concept Convergence and Word Divergence |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Semi-Black Box: Rapid Development of Planning Based Solutions |
❌ |
❌ |
❌ |
❌ |
✅ |
❌ |
✅ |
2 |
| Semi-Distantly Supervised Neural Model for Generating Compact Answers to Open-Domain Why Questions |
❌ |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
3 |
| Semi-Supervised AUC Optimization Without Guessing Labels of Unlabeled Data |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Semi-Supervised Bayesian Attribute Learning for Person Re-Identification |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Semi-Supervised Biomedical Translation With Cycle Wasserstein Regression GANs |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Semi-Supervised Learning From Crowds Using Deep Generative Models |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Sensor-Based Activity Recognition via Learning From Distributions |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Sentence Ordering and Coherence Modeling using Recurrent Neural Networks |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| SenticNet 5: Discovering Conceptual Primitives for Sentiment Analysis by Means of Context Embeddings |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Sentiment Analysis via Deep Hybrid Textual-Crowd Learning Model |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Sequence-to-Point Learning With Neural Networks for Non-Intrusive Load Monitoring |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Sequence-to-Sequence Learning via Shared Latent Representation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Sequential Copying Networks |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
4 |
| Show, Reward and Tell: Automatic Generation of Narrative Paragraph From Photo Stream by Adversarial Training |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Single-Peakedness and Total Unimodularity: New Polynomial-Time Algorithms for Multi-Winner Elections |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Situation Calculus Semantics for Actual Causality |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| SkipFlow: Incorporating Neural Coherence Features for End-to-End Automatic Text Scoring |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Slim Embedding Layers for Recurrent Neural Language Models |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Social Norms of Cooperation With Costly Reputation Building |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Social Recommendation with an Essential Preference Space |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Source Traces for Temporal Difference Learning |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Source-Target Inference Models for Spatial Instruction Understanding |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Sparse Gaussian Conditional Random Fields on Top of Recurrent Neural Networks |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Sparse Modeling-Based Sequential Ensemble Learning for Effective Outlier Detection in High-Dimensional Numeric Data |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Spatial as Deep: Spatial CNN for Traffic Scene Understanding |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
5 |
| Spatio-Temporal Graph Convolution for Skeleton Based Action Recognition |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Spatiotemporal Activity Modeling Under Data Scarcity: A Graph-Regularized Cross-Modal Embedding Approach |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Spectral Word Embedding with Negative Sampling |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Splitting an LPMLN Program |
✅ |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
2 |
| SqueezedText: A Real-Time Scene Text Recognition by Binary Convolutional Encoder-Decoder Network |
❌ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
4 |
| Stack-Captioning: Coarse-to-Fine Learning for Image Captioning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Stackelberg Planning: Towards Effective Leader-Follower State Space Search |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
3 |
| StarSpace: Embed All The Things! |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| State of the Art: Reproducibility in Artificial Intelligence |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Statistical Inference Using SGD |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Stochastic Non-Convex Ordinal Embedding With Stabilized Barzilai-Borwein Step Size |
✅ |
✅ |
✅ |
✅ |
✅ |
✅ |
✅ |
7 |
| Strategic Coalitions With Perfect Recall |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Strategic Coordination of Human Patrollers and Mobile Sensors With Signaling for Security Games |
✅ |
❌ |
❌ |
❌ |
✅ |
✅ |
✅ |
4 |
| Stream Reasoning in Temporal Datalog |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Streaming Non-Monotone Submodular Maximization: Personalized Video Summarization on the Fly |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Structural Deep Embedding for Hyper-Networks |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Style Transfer in Text: Exploration and Evaluation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Subgraph Pattern Neural Networks for High-Order Graph Evolution Prediction |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Sublinear Search Spaces for Shortest Path Planning in Grid and Road Networks |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Submodular Function Maximization Over Graphs via Zero-Suppressed Binary Decision Diagrams |
✅ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
4 |
| Substructure Assembling Network for Graph Classification |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Sum-Product Autoencoding: Encoding and Decoding Representations Using Sum-Product Networks |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Supervised Deep Hashing for Hierarchical Labeled Data |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Sweep-Based Propagation for String Constraint Solving |
✅ |
✅ |
❌ |
❌ |
✅ |
✅ |
✅ |
5 |
| Syntax-Directed Attention for Neural Machine Translation |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Synthesis of Orchestrations of Transducers for Manufacturing |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Synthesis of Programs from Multimodal Datasets |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| T-C3D: Temporal Convolutional 3D Network for Real-Time Action Recognition |
❌ |
✅ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| TIMERS: Error-Bounded SVD Restart on Dynamic Networks |
✅ |
✅ |
✅ |
❌ |
✅ |
❌ |
✅ |
5 |
| Table-to-Text Generation by Structure-Aware Seq2seq Learning |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
✅ |
5 |
| Table-to-Text: Describing Table Region With Natural Language |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Tap and Shoot Segmentation |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Targeted Aspect-Based Sentiment Analysis via Embedding Commonsense Knowledge into an Attentive LSTM |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Task-Aware Compressed Sensing With Generative Adversarial Networks |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
4 |
| Task-Specific Representation Learning for Web-Scale Entity Disambiguation |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Tau-FPL: Tolerance-Constrained Learning in Linear Time |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
4 |
| Teaching a Machine to Read Maps With Deep Reinforcement Learning |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| Telepath: Understanding Users from a Human Vision Perspective in Large-Scale Recommender Systems |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Temporal-Difference Learning With Sampling Baseline for Image Captioning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Temporal-Enhanced Convolutional Network for Person Re-Identification |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Tensorized Projection for High-Dimensional Binary Embedding |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| The Complexity of Bribery in Network-Based Rating Systems |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| The Conference Paper Assignment Problem: Using Order Weighted Averages to Assign Indivisible Goods |
✅ |
❌ |
✅ |
❌ |
❌ |
✅ |
✅ |
4 |
| The Geometric Block Model |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| The Role of Data-Driven Priors in Multi-Agent Crowd Trajectory Estimation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| The Shape of Art History in the Eyes of the Machine |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| The Structural Affinity Method for Solving the Raven’s Progressive Matrices Test for Intelligence |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Thinking in PolAR Pictures: Using Rotation-Friendly Mental Images to Solve Leiter-R Form Completion |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Tool Auctions |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Top-Down Feedback for Crowd Counting Convolutional Neural Network |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Topic Modeling on Health Journals With Regularized Variational Inference |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| TorusE: Knowledge Graph Embedding on a Lie Group |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Toward Deep Reinforcement Learning Without a Simulator: An Autonomous Steering Example |
❌ |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
3 |
| Towards Affordable Semantic Searching: Zero-Shot Retrieval via Dominant Attributes |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Towards Automatic Learning of Procedures From Web Instructional Videos |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Towards Building Large Scale Multimodal Domain-Aware Conversation Systems |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Towards Efficient Detection of Overlapping Communities in Massive Networks |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Towards Formal Definitions of Blameworthiness, Intention, and Moral Responsibility |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Towards Generalization in QBF Solving via Machine Learning |
✅ |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
5 |
| Towards Imperceptible and Robust Adversarial Example Attacks Against Neural Networks |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Towards Perceptual Image Dehazing by Physics-Based Disentanglement and Adversarial Training |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| Towards Training Probabilistic Topic Models on Neuromorphic Multi-Chip Systems |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Towards Ultra-High Performance and Energy Efficiency of Deep Learning Systems: An Algorithm-Hardware Co-Optimization Framework |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
2 |
| Towards a Neural Conversation Model With Diversity Net Using Determinantal Point Processes |
✅ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
3 |
| Towards a Unified Framework for Syntactic Inconsistency Measures |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Trace Ratio Optimization With Feature Correlation Mining for Multiclass Discriminant Analysis |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Tracking Occluded Objects and Recovering Incomplete Trajectories by Reasoning About Containment Relations and Human Actions |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Traffic Optimization for a Mixture of Self-Interested and Compliant Agents |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Training CNNs With Normalized Kernels |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
2 |
| Training Set Debugging Using Trusted Items |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
4 |
| Training and Evaluating Improved Dependency-Based Word Embeddings |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
✅ |
2 |
| Transfer Adversarial Hashing for Hamming Space Retrieval |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Transferable Contextual Bandit for Cross-Domain Recommendation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Transferable Semi-Supervised Semantic Segmentation |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Transferring Decomposed Tensors for Scalable Energy Breakdown Across Regions |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Translating Pro-Drop Languages With Reconstruction Models |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Tree-Structured Neural Machine for Linguistics-Aware Sentence Generation |
✅ |
❌ |
❌ |
✅ |
✅ |
❌ |
✅ |
4 |
| Truthful and Near-Optimal Mechanisms for Welfare Maximization in Multi-Winner Elections |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Twitter Summarization Based on Social Network and Sparse Reconstruction |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Two Knowledge-based Methods for High-Performance Sense Distribution Learning |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| UnFlow: Unsupervised Learning of Optical Flow With a Bidirectional Census Loss |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Understanding Human Behaviors in Crowds by Imitating the Decision-Making Process |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Understanding Image Impressiveness Inspired by Instantaneous Human Perceptual Cues |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Understanding Over Participation in Simple Contests |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Understanding Social Interpersonal Interaction via Synchronization Templates of Facial Events |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Unified Locally Linear Classifiers With Diversity-Promoting Anchor Points |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Unified Spectral Clustering With Optimal Graph |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Unity in Diversity: Learning Distributed Heterogeneous Sentence Representation for Extractive Summarization |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Unravelling Robustness of Deep Learning Based Face Recognition Against Adversarial Attacks |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Unsupervised Articulated Skeleton Extraction From Point Set Sequences Captured by a Single Depth Camera |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Unsupervised Deep Learning of Mid-Level Video Representation for Action Recognition |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Unsupervised Domain Adaptation With Distribution Matching Machines |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Unsupervised Generative Adversarial Cross-Modal Hashing |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Unsupervised Learning of Geometry From Videos With Edge-Aware Depth-Normal Consistency |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| Unsupervised Part-Based Weighting Aggregation of Deep Convolutional Features for Image Retrieval |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Unsupervised Personalized Feature Selection |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Unsupervised Representation Learning With Long-Term Dynamics for Skeleton Based Action Recognition |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Unsupervised Selection of Negative Examples for Grounded Language Learning |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
✅ |
2 |
| Uplink Communication Efficient Differentially Private Sparse Optimization With Feature-Wise Distributed Data |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| Urban Dreams of Migrants: A Case Study of Migrant Integration in Shanghai |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
✅ |
1 |
| Using Syntax to Ground Referring Expressions in Natural Images |
✅ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
5 |
| Using k-Way Co-Occurrences for Learning Word Embeddings |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Utilitarians Without Utilities: Maximizing Social Welfare for Graph Problems Using Only Ordinal Preferences |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| VSE-ens: Visual-Semantic Embeddings with Efficient Negative Sampling |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Variational BOLT: Approximate Learning in Factorial Hidden Markov Models With Application to Energy Disaggregation |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Variational Probability Flow for Biologically Plausible Training of Deep Neural Networks |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| Variational Reasoning for Question Answering With Knowledge Graph |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| Variational Recurrent Neural Machine Translation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Verifying Properties of Binarized Deep Neural Networks |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| Video Generation From Text |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Video Summarization via Semantic Attended Networks |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Video-Based Person Re-Identification via Self Paced Weighting |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
❌ |
1 |
| Video-Based Sign Language Recognition Without Temporal Segmentation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Visual Explanation by High-Level Abduction: On Answer-Set Programming Driven Reasoning About Moving Objects |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
❌ |
2 |
| Visual Relationship Detection With Deep Structural Ranking |
❌ |
❌ |
✅ |
❌ |
✅ |
❌ |
✅ |
3 |
| WalkRanker: A Unified Pairwise Ranking Model With Multiple Relations for Item Recommendation |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Warmstarting of Model-Based Algorithm Configuration |
✅ |
✅ |
✅ |
✅ |
✅ |
✅ |
✅ |
7 |
| Wasserstein Distance Guided Representation Learning for Domain Adaptation |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| Weakly Supervised Collective Feature Learning From Curated Media |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| Weakly Supervised Induction of Affective Events by Optimizing Semantic Consistency |
✅ |
❌ |
✅ |
✅ |
❌ |
✅ |
✅ |
5 |
| Weakly Supervised Salient Object Detection Using Image Labels |
✅ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
5 |
| Weighted Abstract Dialectical Frameworks |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
0 |
| Weighted Multi-View Spectral Clustering Based on Spectral Perturbation |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| Weighted Voting Via No-Regret Learning |
✅ |
❌ |
❌ |
❌ |
❌ |
❌ |
❌ |
1 |
| When Social Advertising Meets Viral Marketing: Sequencing Social Advertisements for Influence Maximization |
✅ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
3 |
| When Waiting Is Not an Option: Learning Options With a Deliberation Cost |
✅ |
✅ |
✅ |
❌ |
❌ |
❌ |
✅ |
4 |
| When Will You Arrive? Estimating Travel Time Based on Deep Neural Networks |
❌ |
✅ |
❌ |
✅ |
✅ |
✅ |
✅ |
5 |
| Who Said What: Modeling Individual Labelers Improves Classification |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
✅ |
3 |
| WiFi-Based Human Identification via Convex Tensor Shapelet Learning |
❌ |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
1 |
| Word Attention for Sequence to Sequence Text Understanding |
❌ |
❌ |
✅ |
✅ |
✅ |
✅ |
✅ |
5 |
| Word Co-Occurrence Regularized Non-Negative Matrix Tri-Factorization for Text Data Co-Clustering |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| Zero-Resource Neural Machine Translation with Multi-Agent Communication Game |
✅ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
3 |
| Zero-Shot Learning With Attribute Selection |
❌ |
❌ |
✅ |
✅ |
❌ |
❌ |
❌ |
2 |
| Zero-Shot Learning via Class-Conditioned Deep Generative Models |
❌ |
❌ |
✅ |
✅ |
✅ |
❌ |
✅ |
4 |
| cw2vec: Learning Chinese Word Embeddings with Stroke n-gram Information |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| gOCCF: Graph-Theoretic One-Class Collaborative Filtering Based on Uninteresting Items |
❌ |
✅ |
✅ |
✅ |
❌ |
❌ |
✅ |
4 |
| r-BTN: Cross-Domain Face Composite and Synthesis From Limited Facial Patches |
❌ |
❌ |
✅ |
❌ |
❌ |
❌ |
✅ |
2 |
| totSAT – Totally-Ordered Hierarchical Planning Through SAT |
❌ |
✅ |
❌ |
❌ |
✅ |
❌ |
❌ |
2 |