variational inequality

Optimal Extragradient-Based Algorithms for Stochastic Variational Inequalities with Separable Structure NeurIPS 2023 Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities NeurIPS 2023 Single-Call Stochastic Extragradient Methods for Structured Non-monotone Variational Inequalities: Improved Analysis under Weaker Conditions NeurIPS 2023 Solving stochastic weak Minty variational inequalities without increasing batch size ICLR 2023 Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods AISTATS 2023 Adaptive and Universal Algorithms for Variational Inequalities with Optimal Convergence AAAI 2022 A Unifying Framework for Variance-Reduced Algorithms for Findings Zeroes of Monotone operators JMLR 2022 Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise NeurIPS 2022 Decentralized Local Stochastic Extra-Gradient for Variational Inequalities NeurIPS 2022 Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees NeurIPS 2022 Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems ICLR 2022 Extragradient Method: O(1/K) Last-Iterate Convergence for Monotone Variational Inequalities and Connections With Cocoercivity AISTATS 2022 Last-Iterate Convergence of Optimistic Gradient Method for Monotone Variational Inequalities NeurIPS 2022 Optimal Algorithms for Decentralized Stochastic Variational Inequalities NeurIPS 2022 Stochastic Extragradient: General Analysis and Improved Rates AISTATS 2022 Stochastic Variance Reduction for Variational Inequality Methods COLT 2022 Adaptive Gradient Methods for Constrained Convex Optimization and Variational Inequalities AAAI 2021 First-order Convergence Theory for Weakly-Convex-Weakly-Concave Min-max Problems JMLR 2021 Sifting through the noise: Universal first-order methods for stochastic variational inequalities NeurIPS 2021 Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity NeurIPS 2021 The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities COLT 2021 End-to-End Learning and Intervention in Games NeurIPS 2020 Halpern Iteration for Near-Optimal and Parameter-Free Monotone Inclusion and Strong Solutions to Variational Inequalities COLT 2020 Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities NeurIPS 2020 Revisiting Stochastic Extragradient AISTATS 2020