{"total":33,"rows":[{"id":"2105.03793","title":"Stability and Generalization of Stochastic Gradient Methods for Minimax Problems","created":"2021-05-08","cited_by_count":36,"area":null},{"id":"2207.08768","title":"Rank-based Decomposable Losses in Machine Learning: A Survey","created":"2022-07-18","cited_by_count":26,"area":null},{"id":"2201.08304","title":"Minimax Demographic Group Fairness in Federated Learning","created":"2022-01-20","cited_by_count":24,"area":null},{"id":"2202.01906","title":"Net benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcare","created":"2022-02-03","cited_by_count":16,"area":null},{"id":"2310.03324","title":"Investigating the Limitation of CLIP Models: The Worst-Performing Categories","created":"2023-10-05","cited_by_count":12,"area":null},{"id":"2107.04641","title":"Training Over-parameterized Models with Non-decomposable Objectives","created":"2021-07-09","cited_by_count":11,"area":null},{"id":"2310.00708","title":"A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm","created":"2023-10-01","cited_by_count":10,"area":null},{"id":"2110.01999","title":"Federating for Learning Group Fair Models","created":"2021-10-05","cited_by_count":9,"area":null},{"id":"2111.08862","title":"Max-Min Grouped Bandits","created":"2021-11-17","cited_by_count":7,"area":null},{"id":"2201.05286","title":"Demystifying Swarm Learning: A New Paradigm of Blockchain-based Decentralized Federated Learning","created":"2022-01-14","cited_by_count":7,"area":null},{"id":"2305.05816","title":"Best-Effort Adaptation","created":"2023-05-10","cited_by_count":7,"area":null},{"id":"2404.05579","title":"DRoP: Distributionally Robust Data Pruning","created":"2024-04-08","cited_by_count":7,"area":null},{"id":"2111.01262","title":"Minimax Optimization: The Case of Convex-Submodular","created":"2021-11-01","cited_by_count":5,"area":null},{"id":"2203.09607","title":"Learning Distributionally Robust Models at Scale via Composite Optimization","created":"2022-03-17","cited_by_count":5,"area":null},{"id":"2102.08454","title":"Lexicographically Fair Learning: Algorithms and Generalization","created":"2021-02-16","cited_by_count":4,"area":null},{"id":"2312.00486","title":"REDUCR: Robust Data Downsampling Using Class Priority Reweighting","created":"2023-12-01","cited_by_count":3,"area":null},{"id":"2102.11911","title":"Instance Specific Approximations for Submodular Maximization","created":"2021-02-23","cited_by_count":2,"area":null},{"id":"2204.04858","title":"Stability and Generalization of Differentially Private Minimax Problems","created":"2022-04-11","cited_by_count":2,"area":null},{"id":"2211.00980","title":"Balancing Utility and Fairness in Submodular Maximization (Technical Report)","created":"2022-11-02","cited_by_count":2,"area":null},{"id":"2212.10318","title":"Learned-Database Systems Security","created":"2022-12-20","cited_by_count":2,"area":null},{"id":"2308.09604","title":"Faster Stochastic Variance Reduction Methods for Compositional MiniMax Optimization","created":"2023-08-18","cited_by_count":2,"area":null},{"id":"2405.05461","title":"Taking a Moment for Distributional Robustness","created":"2024-05-08","cited_by_count":1,"area":null},{"id":"2410.08497","title":"Towards Sharper Risk Bounds for Minimax Problems","created":"2024-10-11","cited_by_count":1,"area":null},{"id":"2505.22703","title":"Private Rate-Constrained Optimization with Applications to Fair Learning","created":"2025-05-28","cited_by_count":1,"area":null},{"id":"2506.03062","title":"Multi-Metric Adaptive Experimental Design Under a Fixed Budget with Validation","created":"2025-06-03","cited_by_count":1,"area":null},{"id":"2509.05811","title":"Simple Optimizers for Convex Aligned Multi-Objective Optimization","created":"2025-09-06","cited_by_count":1,"area":null},{"id":"2101.11443","title":"Adversaries in Online Learning Revisited: with applications in Robust Optimization and Adversarial training","created":"2021-01-27","cited_by_count":0,"area":null},{"id":"2311.01591","title":"Fair Graph Machine Learning under Adversarial Missingness Processes","created":"2023-11-02","cited_by_count":0,"area":null},{"id":"2411.03068","title":"Alpha and Prejudice: Improving $\\alpha$-sized Worst-case Fairness via Intrinsic Reweighting","created":"2024-11-05","cited_by_count":0,"area":null},{"id":"2503.18358","title":"Cost-Sensitive Learning for Long-Tailed Temporal Action Segmentation","created":"2025-03-24","cited_by_count":0,"area":null},{"id":"2511.08419","title":"Probabilistic Safety Guarantee for Stochastic Control Systems Using Average Reward MDPs","created":"2025-11-11","cited_by_count":0,"area":null},{"id":"2607.25299","title":"Retraction-Free Optimization over the Stiefel Manifold for the LoRA Fine-Tuning","created":"2026-07-28","cited_by_count":0,"area":null},{"id":"2610.19322","title":"Generalization Analysis of Biased Stochastic Gradient Methods for Minimax Problems","created":"2026-10-14","cited_by_count":0,"area":null}],"next_cursor":null}