{"total":140,"rows":[{"id":"2103.05180","title":"An Introduction to Deep Generative Modeling","created":"2021-03-09","cited_by_count":104,"area":null},{"id":"2101.04233","title":"Independent Policy Gradient Methods for Competitive Reinforcement Learning","created":"2021-01-11","cited_by_count":101,"area":null},{"id":"2301.10945","title":"A Fully First-Order Method for Stochastic Bilevel Optimization","created":"2023-01-26","cited_by_count":100,"area":null},{"id":"2205.02215","title":"FedNest: Federated Bilevel, Minimax, and Compositional Optimization","created":"2022-05-04","cited_by_count":60,"area":null},{"id":"2104.12761","title":"Adaptive Learning in Continuous Games: Optimal Regret Bounds and Convergence to Nash Equilibrium","created":"2021-04-26","cited_by_count":51,"area":null},{"id":"2309.01753","title":"On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation","created":"2023-09-04","cited_by_count":51,"area":null},{"id":"2102.08352","title":"Stochastic Variance Reduction for Variational Inequality Methods","created":"2021-02-16","cited_by_count":47,"area":null},{"id":"2103.15888","title":"The Complexity of Nonconvex-Strongly-Concave Minimax Optimization","created":"2021-03-29","cited_by_count":45,"area":null},{"id":"2107.00052","title":"Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity","created":"2021-06-30","cited_by_count":43,"area":null},{"id":"2102.13152","title":"Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency","created":"2021-02-25","cited_by_count":40,"area":null},{"id":"2202.07262","title":"Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods","created":"2022-02-15","cited_by_count":37,"area":null},{"id":"2104.08708","title":"Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization","created":"2021-04-18","cited_by_count":36,"area":null},{"id":"2403.08335","title":"A Sparsity Principle for Partially Observable Causal Representation Learning","created":"2024-03-13","cited_by_count":35,"area":null},{"id":"2302.00194","title":"Free Lunch for Domain Adversarial Training: Environment Label Smoothing","created":"2023-02-01","cited_by_count":33,"area":null},{"id":"2102.09468","title":"Near-optimal Local Convergence of Alternating Gradient Descent-Ascent for Minimax Optimization","created":"2021-02-18","cited_by_count":31,"area":null},{"id":"2111.08611","title":"Stochastic Extragradient: General Analysis and Improved Rates","created":"2021-11-16","cited_by_count":31,"area":null},{"id":"2208.04425","title":"Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints","created":"2022-08-08","cited_by_count":25,"area":null},{"id":"2206.03922","title":"A unified stochastic approximation framework for learning in games","created":"2022-06-08","cited_by_count":23,"area":null},{"id":"2106.13781","title":"Tighter Analysis of Alternating Stochastic Gradient Method for Stochastic Nested Problems","created":"2021-06-25","cited_by_count":22,"area":null},{"id":"2106.12928","title":"Exploration-Exploitation in Multi-Agent Competition: Convergence with Bounded Rationality","created":"2021-06-24","cited_by_count":21,"area":null},{"id":"2302.09831","title":"Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems","created":"2023-02-20","cited_by_count":21,"area":null},{"id":"2111.11309","title":"No-Regret Dynamics in the Fenchel Game: A Unified Framework for Algorithmic Convex Optimization","created":"2021-11-22","cited_by_count":20,"area":null},{"id":"2205.05653","title":"The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization","created":"2022-05-11","cited_by_count":20,"area":null},{"id":"2302.01275","title":"ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs","created":"2023-02-02","cited_by_count":20,"area":null},{"id":"2204.09228","title":"Tight Last-Iterate Convergence of the Extragradient and the Optimistic Gradient Descent-Ascent Algorithm for Constrained Monotone Variational Inequalities","created":"2022-04-20","cited_by_count":19,"area":null},{"id":"2107.00464","title":"On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging","created":"2021-06-30","cited_by_count":18,"area":null},{"id":"2106.01761","title":"Near Optimal Stochastic Algorithms for Finite-Sum Unbalanced Convex-Concave Minimax Optimization","created":"2021-06-03","cited_by_count":16,"area":null},{"id":"2112.15199","title":"Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling","created":"2021-12-30","cited_by_count":16,"area":null},{"id":"2202.09674","title":"Generalized Optimistic Methods for Convex-Concave Saddle Point Problems","created":"2022-02-19","cited_by_count":16,"area":null},{"id":"2205.01780","title":"The ICML 2022 Expressive Vocalizations Workshop and Competition: Recognizing, Generating, and Personalizing Vocal Bursts","created":"2022-05-03","cited_by_count":16,"area":null},{"id":"2206.00743","title":"Nest Your Adaptive Algorithm for Parameter-Agnostic Nonconvex Minimax Optimization","created":"2022-06-01","cited_by_count":16,"area":null},{"id":"2402.13903","title":"Dealing with unbounded gradients in stochastic saddle-point optimization","created":"2024-02-21","cited_by_count":16,"area":null},{"id":"2110.03313","title":"Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees","created":"2021-10-07","cited_by_count":15,"area":null},{"id":"2202.02771","title":"Optimal Algorithms for Decentralized Stochastic Variational Inequalities","created":"2022-02-06","cited_by_count":14,"area":null},{"id":"2206.01095","title":"Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise","created":"2022-06-02","cited_by_count":14,"area":null},{"id":"2211.01280","title":"An Exponentially Converging Particle Method for the Mixed Nash Equilibrium of Continuous Games","created":"2022-11-02","cited_by_count":14,"area":null},{"id":"2302.14043","title":"Single-Call Stochastic Extragradient Methods for Structured Non-monotone Variational Inequalities: Improved Analysis under Weaker Conditions","created":"2023-02-27","cited_by_count":14,"area":null},{"id":"2305.15938","title":"First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities","created":"2023-05-25","cited_by_count":14,"area":null},{"id":"2201.07427","title":"Lifted Primal-Dual Method for Bilinearly Coupled Smooth Minimax Optimization","created":"2022-01-19","cited_by_count":13,"area":null},{"id":"2107.01906","title":"The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities","created":"2021-07-05","cited_by_count":12,"area":null},{"id":"2212.12978","title":"Universal Gradient Descent Ascent Method for Nonconvex-Nonconcave Minimax Optimization","created":"2022-12-26","cited_by_count":12,"area":null},{"id":"2402.07101","title":"On the Complexity of First-Order Methods in Stochastic Bilevel Optimization","created":"2024-02-11","cited_by_count":12,"area":null},{"id":"2406.04558","title":"On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization","created":"2024-06-07","cited_by_count":12,"area":null},{"id":"2101.08367","title":"Influence Estimation for Generative Adversarial Networks","created":"2021-01-20","cited_by_count":11,"area":null},{"id":"2102.08431","title":"Complex Momentum for Optimization in Games","created":"2021-02-16","cited_by_count":11,"area":null},{"id":"2103.03405","title":"Learning in Matrix Games can be Arbitrarily Complex","created":"2021-03-05","cited_by_count":11,"area":null},{"id":"2211.13668","title":"Zeroth-Order Alternating Gradient Descent Ascent Algorithms for a Class of Nonconvex-Nonconcave Minimax Problems","created":"2022-11-24","cited_by_count":11,"area":null},{"id":"2504.01212","title":"Cooper: A Library for Constrained Optimization in Deep Learning","created":"2025-04-01","cited_by_count":11,"area":null},{"id":"2208.13592","title":"Smooth Monotone Stochastic Variational Inequalities and Saddle Point Problems: A Survey","created":"2022-08-29","cited_by_count":10,"area":null},{"id":"2109.14213","title":"On the One-sided Convergence of Adam-type Algorithms in Non-convex Non-concave Min-max Optimization","created":"2021-09-29","cited_by_count":9,"area":null},{"id":"2110.05192","title":"Convex-Concave Min-Max Stackelberg Games","created":"2021-10-05","cited_by_count":9,"area":null},{"id":"2202.06950","title":"Sion's Minimax Theorem in Geodesic Metric Spaces and a Riemannian Extragradient Algorithm","created":"2022-02-13","cited_by_count":9,"area":null},{"id":"2206.01132","title":"A Communication-efficient Algorithm with Linear Convergence for Federated Minimax Learning","created":"2022-06-02","cited_by_count":9,"area":null},{"id":"2207.00957","title":"On Convergence of Gradient Descent Ascent: A Tight Local Analysis","created":"2022-07-03","cited_by_count":9,"area":null},{"id":"2402.10475","title":"Fundamental Benefit of Alternating Updates in Minimax Optimization","created":"2024-02-16","cited_by_count":9,"area":null},{"id":"2101.05248","title":"Solving Min-Max Optimization with Hidden Structure via Gradient Descent Ascent","created":"2021-01-13","cited_by_count":8,"area":null},{"id":"2112.14570","title":"Lyapunov Exponents for Diversity in Differentiable Games","created":"2021-12-24","cited_by_count":8,"area":null},{"id":"2206.09446","title":"Compression and Data Similarity: Combination of Two Techniques for Communication-Efficient Solving of Distributed Variational Inequalities","created":"2022-06-19","cited_by_count":8,"area":null},{"id":"2210.17478","title":"TiAda: A Time-scale Adaptive Algorithm for Nonconvex Minimax Optimization","created":"2022-10-31","cited_by_count":8,"area":null},{"id":"2301.02060","title":"A first-order augmented Lagrangian method for constrained minimax optimization","created":"2023-01-05","cited_by_count":8,"area":null},{"id":"2406.02016","title":"Adaptive and Optimal Second-order Optimistic Methods for Minimax Optimization","created":"2024-06-04","cited_by_count":8,"area":null},{"id":"2108.00473","title":"Derivative-free Alternating Projection Algorithms for General Nonconvex-Concave Minimax Problems","created":"2021-08-01","cited_by_count":7,"area":null},{"id":"2202.05352","title":"Domain Adversarial Training: A Game Perspective","created":"2022-02-10","cited_by_count":7,"area":null},{"id":"2203.02770","title":"Don't Be So Dense: Sparse-to-Sparse GAN Training Without Sacrificing Performance","created":"2022-03-05","cited_by_count":7,"area":null},{"id":"2210.09382","title":"Tight Analysis of Extra-gradient and Optimistic Gradient Methods For Nonconvex Minimax Problems","created":"2022-10-17","cited_by_count":7,"area":null},{"id":"2302.07615","title":"Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities","created":"2023-02-15","cited_by_count":7,"area":null},{"id":"2310.20673","title":"Balancing Act: Constraining Disparate Impact in Sparse Models","created":"2023-10-31","cited_by_count":7,"area":null},{"id":"2402.12416","title":"Aligning Individual and Collective Objectives in Multi-Agent Cooperation","created":"2024-02-19","cited_by_count":7,"area":null},{"id":"2512.15134","title":"From Isolation to Entanglement: When Do Interpretability Methods Identify and Disentangle Known Concepts?","created":"2025-12-17","cited_by_count":7,"area":null},{"id":"2103.08270","title":"DIPPA: An improved Method for Bilinear Saddle Point Problems","created":"2021-03-15","cited_by_count":6,"area":null},{"id":"2106.03579","title":"Forward Looking Best-Response Multiplicative Weights Update Methods for Bilinear Zero-sum Games","created":"2021-06-07","cited_by_count":6,"area":null},{"id":"2306.16502","title":"Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements","created":"2023-06-28","cited_by_count":6,"area":null},{"id":"2402.12508","title":"SDEs for Minimax Optimization","created":"2024-02-19","cited_by_count":6,"area":null},{"id":"2202.10600","title":"Myriad: a real-world testbed to bridge trajectory optimization and deep learning","created":"2022-02-22","cited_by_count":5,"area":null},{"id":"2203.14126","title":"Robust No-Regret Learning in Min-Max Stackelberg Games","created":"2022-03-26","cited_by_count":5,"area":null},{"id":"2303.17192","title":"Sublinear Convergence Rates of Extragradient-Type Methods: A Survey on Classical and Recent Developments","created":"2023-03-30","cited_by_count":5,"area":null},{"id":"2501.08263","title":"Multiplayer Federated Learning: Reaching Equilibrium with Less Communication","created":"2025-01-14","cited_by_count":5,"area":null},{"id":"2106.07289","title":"Decentralized Personalized Federated Learning for Min-Max Problems","created":"2021-06-14","cited_by_count":4,"area":null},{"id":"2203.14129","title":"Nash, Conley, and Computation: Impossibility and Incompleteness in Game Dynamics","created":"2022-03-26","cited_by_count":4,"area":null},{"id":"2206.08573","title":"Optimal Extragradient-Based Bilinearly-Coupled Saddle-Point Optimization","created":"2022-06-17","cited_by_count":4,"area":null},{"id":"2301.03931","title":"Min-Max Optimization Made Simple: Approximating the Proximal Point Method via Contraction Maps","created":"2023-01-10","cited_by_count":4,"area":null},{"id":"2305.16186","title":"Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties","created":"2023-05-25","cited_by_count":4,"area":null},{"id":"2311.02407","title":"The equivalence of dynamic and strategic stability under regularized learning in games","created":"2023-11-04","cited_by_count":4,"area":null},{"id":"2403.09090","title":"Dissipative Gradient Descent Ascent Method: A Control Theory Inspired Algorithm for Min-max Optimization","created":"2024-03-14","cited_by_count":4,"area":null},{"id":"2412.20203","title":"No-regret learning in harmonic games: Extrapolation in the face of conflicting interests","created":"2024-12-28","cited_by_count":4,"area":null},{"id":"2605.18809","title":"Metric-Gradient Projection for Stable Multi-Agent Policy Learning","created":"2026-05-12","cited_by_count":4,"area":null},{"id":"2103.12685","title":"Generative Minimization Networks: Training GANs Without Competition","created":"2021-03-23","cited_by_count":3,"area":null},{"id":"2206.08303","title":"On Scaled Methods for Saddle Point Problems","created":"2022-06-16","cited_by_count":3,"area":null},{"id":"2206.12563","title":"Generating Diverse Vocal Bursts with StyleGAN2 and MEL-Spectrograms","created":"2022-06-25","cited_by_count":3,"area":null},{"id":"2310.13459","title":"Stable Nonconvex-Nonconcave Training via Linear Interpolation","created":"2023-10-20","cited_by_count":3,"area":null},{"id":"2310.17759","title":"Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization","created":"2023-10-26","cited_by_count":3,"area":null},{"id":"2403.12859","title":"Primal Methods for Variational Inequality Problems with Functional Constraints","created":"2024-03-19","cited_by_count":3,"area":null},{"id":"2507.16279","title":"MAN++: Scaling Momentum Auxiliary Network for Supervised Local Learning in Vision Tasks","created":"2025-07-22","cited_by_count":3,"area":null},{"id":"2510.22421","title":"Extragradient Method for $(L_0, L_1)$-Lipschitz Root-finding Problems","created":"2025-10-25","cited_by_count":3,"area":null},{"id":"2101.01400","title":"Relaxed Conditional Image Transfer for Semi-supervised Domain Adaptation","created":"2021-01-05","cited_by_count":2,"area":null},{"id":"2106.10022","title":"Local AdaGrad-Type Algorithm for Stochastic Convex-Concave Optimization","created":"2021-06-18","cited_by_count":2,"area":null},{"id":"2109.05535","title":"Adversarial Representation Learning With Closed-Form Solvers","created":"2021-09-12","cited_by_count":2,"area":null},{"id":"2204.03187","title":"Distributed Statistical Min-Max Learning in the Presence of Byzantine Agents","created":"2022-04-07","cited_by_count":2,"area":null},{"id":"2210.16482","title":"Recursive Reasoning in Minimax Games: A Level $k$ Gradient Play Method","created":"2022-10-29","cited_by_count":2,"area":null},{"id":"2210.17550","title":"Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization","created":"2022-10-31","cited_by_count":2,"area":null}],"next_cursor":"100"}