{"total":35,"rows":[{"id":"2311.06750","title":"Federated Learning for Generalization, Robustness, Fairness: A Survey and Benchmark","created":"2023-11-12","cited_by_count":99,"area":null},{"id":"2301.01299","title":"Recent Advances on Federated Learning: A Systematic Survey","created":"2023-01-03","cited_by_count":41,"area":null},{"id":"2310.09866","title":"Federated Multi-Objective Learning","created":"2023-10-15","cited_by_count":12,"area":null},{"id":"2210.14396","title":"FeDXL: Provable Federated Learning for Deep X-Risk Optimization","created":"2022-10-26","cited_by_count":11,"area":null},{"id":"2205.15614","title":"Communication-Efficient Distributionally Robust Decentralized Learning","created":"2022-05-31","cited_by_count":10,"area":null},{"id":"2310.03613","title":"Solving a Class of Non-Convex Minimax Optimization in Federated Learning","created":"2023-10-05","cited_by_count":10,"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":"2301.03113","title":"Randomized Block-Coordinate Optimistic Gradient Algorithms for Root-Finding Problems","created":"2023-01-08","cited_by_count":9,"area":null},{"id":"2302.04249","title":"Federated Minimax Optimization with Client Heterogeneity","created":"2023-02-08","cited_by_count":8,"area":null},{"id":"2304.10101","title":"Federated Compositional Deep AUC Maximization","created":"2023-04-20","cited_by_count":8,"area":null},{"id":"2405.00965","title":"Robust Decentralized Learning with Local Updates and Gradient Tracking","created":"2024-05-02","cited_by_count":8,"area":null},{"id":"2205.14278","title":"Generalization Bounds of Nonconvex-(Strongly)-Concave Stochastic Minimax Optimization","created":"2022-05-28","cited_by_count":7,"area":null},{"id":"2211.07303","title":"Adaptive Federated Minimax Optimization with Lower Complexities","created":"2022-11-14","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":"2503.18317","title":"Improved Rates of Differentially Private Nonconvex-Strongly-Concave Minimax Optimization","created":"2025-03-24","cited_by_count":5,"area":null},{"id":"2304.10902","title":"Near-Optimal Decentralized Momentum Method for Nonconvex-PL Minimax Problems","created":"2023-04-21","cited_by_count":4,"area":null},{"id":"2306.05100","title":"Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates","created":"2023-06-08","cited_by_count":4,"area":null},{"id":"2307.14364","title":"Federated Distributionally Robust Optimization with Non-Convex Objectives: Algorithm and Analysis","created":"2023-07-25","cited_by_count":4,"area":null},{"id":"2311.00944","title":"Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization","created":"2023-11-02","cited_by_count":4,"area":null},{"id":"2406.13041","title":"Accelerated Stochastic Min-Max Optimization Based on Bias-corrected Momentum","created":"2024-06-18","cited_by_count":2,"area":null},{"id":"2511.04456","title":"Federated Stochastic Minimax Optimization under Heavy-Tailed Noises","created":"2025-11-06","cited_by_count":2,"area":null},{"id":"2406.02939","title":"Achieving Near-Optimal Convergence for Distributed Minimax Optimization with Adaptive Stepsizes","created":"2024-06-05","cited_by_count":1,"area":null},{"id":"2412.03867","title":"GP-FL: Model-Based Hessian Estimation for Second-Order Over-the-Air Federated Learning","created":"2024-12-05","cited_by_count":1,"area":null},{"id":"2502.16055","title":"MedForge: Building Medical Foundation Models Like Open Source Software Development","created":"2025-02-22","cited_by_count":1,"area":null},{"id":"2505.21012","title":"Federated Instrumental Variable Analysis via Federated Generalized Method of Moments","created":"2025-05-27","cited_by_count":1,"area":null},{"id":"2509.04107","title":"FedQuad: Federated Stochastic Quadruplet Learning to Mitigate Data Heterogeneity","created":"2025-09-04","cited_by_count":1,"area":null},{"id":"2210.00611","title":"SAGDA: Achieving $\\mathcal{O}(\\epsilon^{-2})$ Communication Complexity in Federated Min-Max Learning","created":"2022-10-02","cited_by_count":0,"area":null},{"id":"2305.15643","title":"Federated Composite Saddle Point Optimization","created":"2023-05-25","cited_by_count":0,"area":null},{"id":"2306.01648","title":"Federated Multi-Sequence Stochastic Approximation with Local Hypergradient Estimation","created":"2023-06-02","cited_by_count":0,"area":null},{"id":"2405.04566","title":"Fast Decentralized Gradient Tracking for Federated Minimax Optimization with Local Updates","created":"2024-05-07","cited_by_count":0,"area":null},{"id":"2412.15010","title":"Hybrid-Regularized Magnitude Pruning for Robust Federated Learning under Covariate Shift","created":"2024-12-19","cited_by_count":0,"area":null},{"id":"2501.14652","title":"Decoupled SGDA for Games with Intermittent Strategy Communication","created":"2025-01-24","cited_by_count":0,"area":null},{"id":"2601.01649","title":"Communication-Efficient Federated AUC Maximization with Cyclic Client Participation","created":"2026-01-04","cited_by_count":0,"area":null},{"id":"2605.07888","title":"Enhancing Federated Quadruplet Learning: Stochastic Client Selection and Embedding Stability Analysis","created":"2026-05-08","cited_by_count":0,"area":null},{"id":"2605.26243","title":"Provably Communication-Efficient and Privacy-Preserving Federated Graph Neural Networks","created":"2026-05-25","cited_by_count":0,"area":null}],"next_cursor":null}