saddle point problem

A Natural Primal-Dual Hybrid Gradient Method for Adversarial Neural Network Training on Solving Partial Differential Equation JMLR 2026 Stochastic Decentralized Optimization of Non-Smooth Convex and Convex-Concave Problems over Time-Varying Networks AAAI 2026 Adaptive Extragradient Methods for Root-finding Problems under Relaxed Assumptions AISTATS 2025 High Probability and Risk-Averse Guarantees for a Stochastic Accelerated Primal-Dual Method JMLR 2024 Local Composite Saddle Point Optimization ICLR 2024 Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems extended abstract COLT 2024 Accelerated Primal-Dual Methods for Convex-Strongly-Concave Saddle Point Problems ICML 2023 A Relaxed Inertial Forward-Backward-Forward Algorithm for Solving Monotone Inclusions with Application to GANs JMLR 2023 Randomized Primal-Dual Methods with Adaptive Step Sizes AISTATS 2023 AdAUC: End-to-end Adversarial AUC Optimization Against Long-tail Problems ICML 2022 Quasi-Newton Methods for Saddle Point Problems NeurIPS 2022 Stochastic Variance Reduction for Variational Inequality Methods COLT 2022 Generalization Bounds for Stochastic Saddle Point Problems AISTATS 2021 One-sided Frank-Wolfe algorithms for saddle problems ICML 2021 A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach AISTATS 2020 Efficient Projection-free Algorithms for Saddle Point Problems NeurIPS 2020 Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems COLT 2020 Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave Saddle Point Problems without Strong Convexity AISTATS 2019 Level-Set Methods for Finite-Sum Constrained Convex Optimization ICML 2018 Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization ICML 2015 Identifying and attacking the saddle point problem in high-dimensional non-convex optimization NeurIPS 2014