Optimization

Learning Preconditioners for Conjugate Gradient PDE Solvers ICML 2023 Learning Proximal Operators to Discover Multiple Optima ICLR 2023 Learning Reliable Logical Rules with SATNet NeurIPS 2023 Learning Second-Order Attentive Context for Efficient Correspondence Pruning AAAI 2023 Learning Sparse and Low-Rank Priors for Image Recovery via Iterative Reweighted Least Squares Minimization ICLR 2023 Learning Sparse Graphon Mean Field Games AISTATS 2023 Learning the Efficient Frontier NeurIPS 2023 Learning the Positions in CountSketch ICLR 2023 Learning to CROSS exchange to solve min-max vehicle routing problems ICLR 2023 Learning To Exploit the Sequence-Specific Prior Knowledge for Image Processing Pipelines Optimization CVPR 2023 Learning to Generate Columns with Application to Vertex Coloring ICLR 2023 Learning to Group Auxiliary Datasets for Molecule NeurIPS 2023 Learning-to-Learn to Guide Random Search: Derivative-Free Meta Blackbox Optimization on Manifold L4DC 2023 Learning to Optimize Differentiable Games ICML 2023 Learning to Optimize with Stochastic Dominance Constraints AISTATS 2023 Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt NeurIPS 2023 Learning to Select Pivotal Samples for Meta Re-weighting AAAI 2023 Learning to Suggest Breaks: Sustainable Optimization of Long-Term User Engagement ICML 2023 Learning Unnormalized Statistical Models via Compositional Optimization ICML 2023 Learning When to Speak: Latency and Quality Trade-offs for Simultaneous Speech-to-Speech Translation with Offline Models Interspeech 2023 Learning with Logical Constraints but without Shortcut Satisfaction ICLR 2023 Least Squares Model Averaging for Distributed Data JMLR 2023 Let’s Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs EMNLP 2023 Lexinvariant Language Models NeurIPS 2023 LibMTL: A Python Library for Deep Multi-Task Learning JMLR 2023