convergence rate

Wasserstein F-tests for Frechet regression on Bures-Wasserstein manifolds JMLR 2025 WAVE: Wasserstein Adaptive Value Estimation for Actor-Critic Reinforcement Learning L4DC 2025 When Extragradient Meets PAGE: Bridging Two Giants to Boost Variational Inequalities UAI 2025 Accelerated Algorithms for Constrained Nonconvex-Nonconcave Min-Max Optimization and Comonotone Inclusion ICML 2024 Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement Learning ICML 2024 Accelerating Convergence of Score-Based Diffusion Models, Provably ICML 2024 Acceleration and Implicit Regularization in Gaussian Phase Retrieval AISTATS 2024 Achieving Near-Optimal Convergence for Distributed Minimax Optimization with Adaptive Stepsizes NeurIPS 2024 Adam with model exponential moving average is effective for nonconvex optimization NeurIPS 2024 Adaptive and non-adaptive minimax rates for weighted Laplacian-Eigenmap based nonparametric regression AISTATS 2024 Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization NeurIPS 2024 Adaptive Quasi-Newton and Anderson Acceleration Framework with Explicit Global (Accelerated) Convergence Rates AISTATS 2024 Adaptive Stabilization Based on Machine Learning for Column Generation ICML 2024 Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning ICLR 2024 Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions NeurIPS 2024 ADOPT: Modified Adam Can Converge with Any β_2 with the Optimal Rate NeurIPS 2024 A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization ICML 2024 Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness ICLR 2024 A Fine-grained Analysis of Fitted Q-evaluation: Beyond Parametric Models ICML 2024 A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts ICML 2024 Almost Sure Convergence Rates Analysis and Saddle Avoidance of Stochastic Gradient Methods JMLR 2024 Analysis of Kernel Mirror Prox for Measure Optimization AISTATS 2024 A New Robust Partial p-Wasserstein-Based Metric for Comparing Distributions ICML 2024 A Primal-Dual Approach to Solving Variational Inequalities with General Constraints ICLR 2024 A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers NeurIPS 2024