Optimization

Learning Optimal Lattice Vector Quantizers for End-to-end Neural Image Compression NeurIPS 2024 Learning Pareto Set for Multi-Objective Continuous Robot Control IJCAI 2024 Learning Performance-Improving Code Edits ICLR 2024 Learning Planning-based Reasoning by Trajectories Collection and Process Reward Synthesizing EMNLP 2024 Learning Polynomial Problems with SL(2, R)-Equivariance ICLR 2024 Learning Pseudo-Contractive Denoisers for Inverse Problems ICML 2024 Learning Quadruped Locomotion Using Differentiable Simulation CoRL 2024 Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds ICML 2024 Learning Reduced Fluid Dynamics AAAI 2024 Learning Representation for Multitask Learning through Self-Supervised Auxiliary Learning ECCV 2024 Learning Reward for Robot Skills Using Large Language Models via Self-Alignment ICML 2024 Learning Sampling Policy to Achieve Fewer Queries for Zeroth-Order Optimization AISTATS 2024 Learning Solution-Aware Transformers for Efficiently Solving Quadratic Assignment Problem ICML 2024 Learning Surrogates for Offline Black-Box Optimization via Gradient Matching ICML 2024 Learning the Expected Core of Strictly Convex Stochastic Cooperative Games NeurIPS 2024 Learning the Optimal Policy for Balancing Short-Term and Long-Term Rewards NeurIPS 2024 Learning to Approximate Adaptive Kernel Convolution on Graphs AAAI 2024 Learning to be Smooth: An End-to-End Differentiable Particle Smoother NeurIPS 2024 Learning to Build Solutions in Stochastic Matching Problems Using Flows (Student Abstract) AAAI 2024 Learning to Pivot as a Smart Expert AAAI 2024 Learning to Predict Structural Vibrations NeurIPS 2024 Learning to Reason via Program Generation, Emulation, and Search NeurIPS 2024 Learning to Remove Cuts in Integer Linear Programming ICML 2024 Learning to Reweight for Generalizable Graph Neural Network AAAI 2024 Learning to Solve Bilevel Programs with Binary Tender ICLR 2024