discrete optimization

Injecting Logical Constraints into Neural Networks via Straight-Through Estimators ICML 2022 Integer and Constraint Programming Revisited for Mutually Orthogonal Latin Squares (Student Abstract) AAAI 2022 Joint Continuous and Discrete Model Selection via Submodularity JMLR 2022 Leveraging Inter-Layer Dependency for Post -Training Quantization NeurIPS 2022 Minimax Optimization: The Case of Convex-Submodular AISTATS 2022 Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions NeurIPS 2022 One Loss for Quantization: Deep Hashing With Discrete Wasserstein Distributional Matching CVPR 2022 Online Enhanced Semantic Hashing: Towards Effective and Efficient Retrieval for Streaming Multi-Modal Data AAAI 2022 Optimal channel selection with discrete QCQP AISTATS 2022 Partial Wasserstein Covering AAAI 2022 Scalable design of Error-Correcting Output Codes using Discrete Optimization with Graph Coloring NeurIPS 2022 Adaptive Experimental Design for Optimizing Combinatorial Structures IJCAI 2021 Alternating Direction Method of Multipliers for Quantization AISTATS 2021 Decomposable Submodular Function Minimization via Maximum Flow ICML 2021 Discrete Multiple Kernel k-means IJCAI 2021 Interpretable Sequence Classification via Discrete Optimization AAAI 2021 Learning with Algorithmic Supervision via Continuous Relaxations NeurIPS 2021 Learn The Big Picture: Representation Learning for Clustering ACL 2021 New Algorithms for Japanese Residency Matching IJCAI 2021 Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm NeurIPS 2021 Perturb-and-max-product: Sampling and learning in discrete energy-based models NeurIPS 2021 Practical Null Steering in Millimeter Wave Networks NSDI 2021 Rescuing Deep Hashing from Dead Bits Problem IJCAI 2021 Scaling Up Exact Neural Network Compression by ReLU Stability NeurIPS 2021 Solving Soft Clustering Ensemble via k-Sparse Discrete Wasserstein Barycenter NeurIPS 2021