finite-sum optimization

A New Random Reshuffling Method for Nonsmooth Nonconvex Finite-sum Optimization JMLR 2025 Joint Gradient Balancing for Data Ordering in Finite-Sum Multi-Objective Optimization ICLR 2025 Last-iterate Convergence of Shuffling Momentum Gradient Method under the Kurdyka-Lojasiewicz Inequality JMLR 2025 SIFAR: A Simple Faster Accelerated Variance-Reduced Gradient Method IJCAI 2025 Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations NeurIPS 2024 Lower Complexity Bounds of Finite-Sum Optimization Problems: The Results and Construction JMLR 2024 Quantum Algorithms and Lower Bounds for Finite-Sum Optimization ICML 2024 Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions ICLR 2024 Faster Rates of Convergence to Stationary Points in Differentially Private Optimization ICML 2023 Non-Smooth Weakly-Convex Finite-sum Coupled Compositional Optimization NeurIPS 2023 Adaptive Accelerated (Extra-)Gradient Methods with Variance Reduction ICML 2022 Dimension-free Complexity Bounds for High-order Nonconvex Finite-sum Optimization ICML 2022 Learning Distributionally Robust Models at Scale via Composite Optimization ICLR 2022 On the Oracle Complexity of Higher-Order Smooth Non-Convex Finite-Sum Optimization AISTATS 2022 Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums AISTATS 2022 Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization NeurIPS 2022 SAN: Stochastic Average Newton Algorithm for Minimizing Finite Sums AISTATS 2022 Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods COLT 2022 Theoretical Convergence of Multi-Step Model-Agnostic Meta-Learning JMLR 2022 A Unified Convergence Analysis for Shuffling-Type Gradient Methods JMLR 2021 L-SVRG and L-Katyusha with Arbitrary Sampling JMLR 2021 Adaptive Importance Sampling for Finite-Sum Optimization and Sampling with Decreasing Step-Sizes NeurIPS 2020 DINO: Distributed Newton-Type Optimization Method ICML 2020 How Good is SGD with Random Shuffling? COLT 2020 SGD with shuffling: optimal rates without component convexity and large epoch requirements NeurIPS 2020