Optimization

Accelerating Nuclear-norm Regularized Low-rank Matrix Optimization Through Burer-Monteiro Decomposition JMLR 2024 Accelerating PDE Data Generation via Differential Operator Action in Solution Space ICML 2024 Accelerating Sinkhorn algorithm with sparse Newton iterations ICLR 2024 Acceleration and Implicit Regularization in Gaussian Phase Retrieval AISTATS 2024 Acceleration Exists! Optimization Problems When Oracle Can Only Compare Objective Function Values NeurIPS 2024 Acceleration of Posteriorgram-based DTW by Distilling the Class-to-class Distances Encoded in the Classifier Used to Calculate Posteriors Interspeech 2024 Achieving Group Distributional Robustness and Minimax Group Fairness with Interpolating Classifiers AISTATS 2024 Achieving Margin Maximization Exponentially Fast via Progressive Norm Rescaling ICML 2024 Achieving Near-Optimal Convergence for Distributed Minimax Optimization with Adaptive Stepsizes NeurIPS 2024 Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping ICLR 2024 Achieving Tractable Minimax Optimal Regret in Average Reward MDPs NeurIPS 2024 A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design ICML 2024 A Combinatorial Algorithm for the Semi-Discrete Optimal Transport Problem NeurIPS 2024 A Comparison of Language Modeling and Translation as Multilingual Pretraining Objectives EMNLP 2024 A Comprehensive View of Personalized Federated Learning on Heterogeneous Clinical Datasets MLHC 2024 A Computational Framework for Solving Wasserstein Lagrangian Flows ICML 2024 A connection between Tempering and Entropic Mirror Descent ICML 2024 ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints ICML 2024 Activation-Descent Regularization for Input Optimization of ReLU Networks ICML 2024 Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes NeurIPS 2024 A Cubic-regularized Policy Newton Algorithm for Reinforcement Learning AISTATS 2024 AdaLomo: Low-memory Optimization with Adaptive Learning Rate ACL 2024 Adam-family Methods for Nonsmooth Optimization with Convergence Guarantees JMLR 2024 Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps NeurIPS 2024 Adam with model exponential moving average is effective for nonconvex optimization NeurIPS 2024