convergence rate

Near-Optimal Convex Simple Bilevel Optimization with a Bisection Method AISTATS 2024 Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games AISTATS 2024 Non-convex Stochastic Composite Optimization with Polyak Momentum ICML 2024 Nonparametric Regression for 3D Point Cloud Learning JMLR 2024 Nonsmooth Implicit Differentiation: Deterministic and Stochastic Convergence Rates ICML 2024 No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes UAI 2024 On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions NeurIPS 2024 On Stationary Point Convergence of PPO-Clip ICLR 2024 On the Computational and Statistical Complexity of Over-parameterized Matrix Sensing JMLR 2024 On the Convergence of Loss and Uncertainty-based Active Learning Algorithms NeurIPS 2024 On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity ICML 2024 On the Hyperparameters in Stochastic Gradient Descent with Momentum JMLR 2024 On the Saturation Effects of Spectral Algorithms in Large Dimensions NeurIPS 2024 Open Problem: Anytime Convergence Rate of Gradient Descent COLT 2024 Optimal First-Order Algorithms as a Function of Inequalities JMLR 2024 Optimal Locally Private Nonparametric Classification with Public Data JMLR 2024 Optimization without Retraction on the Random Generalized Stiefel Manifold ICML 2024 Optimizing ADMM and Over-Relaxed ADMM Parameters for Linear Quadratic Problems AAAI 2024 Parameter-Agnostic Optimization under Relaxed Smoothness AISTATS 2024 Parameter-free Clipped Gradient Descent Meets Polyak NeurIPS 2024 Performative Control for Linear Dynamical Systems NeurIPS 2024 Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts AAAI 2024 Physics-informed machine learning as a kernel method COLT 2024 PILOT: An O(1/K)-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation ICLR 2024 Plug-in Performative Optimization ICML 2024