mlsanityData to 14 Oct 2026

Near-Optimal Algorithms for Group Distributionally Robust Optimization and Beyond

arXiv 2212.13669 ↗First posted 28 Dec 2022cs.LG math.OCcited by 17

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Abstract (arXiv)

Distributionally robust optimization (DRO) can improve the robustness and fairness of learning methods. In this paper, we devise stochastic algorithms for a class of DRO problems including group DRO, subpopulation fairness, and empirical conditional value at risk (CVaR) optimization. Our new algorithms achieve faster convergence rates than existing algorithms for multiple DRO settings. We also provide a new information-theoretic lower bound that implies our bounds are tight for group DRO. Empirically, too, our algorithms outperform known methods.

Key facts. Cited by 17 papers in the map (data through 14 Oct 2026). Builds on 24 of its 38 references that are in the map. First posted on arXiv 28 Dec 2022.

Builds on

24 of 38 references.

References · 24

  1. 2019Optuna: A Next-generation Hyperparameter Optimization Frameworkcited by 2,501
  2. 2020WILDS: A Benchmark of in-the-Wild Distribution Shiftscited by 1,375
  3. 2019Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalizationcited by 1,247
  4. 2019Introduction to Online Convex Optimizationcited by 803
  5. 2019Online Learning: A Modern Introduction Using Convex Optimizationcited by 417
  6. 2018Fairness Without Demographics in Repeated Loss Minimizationcited by 364
  7. 2018Learning Models with Uniform Performance via Distributionally Robust Optimizationcited by 335
  8. 2015Data-driven Distributionally Robust Optimization Using the Wasserstein Metric: Performance Guarantees and Tractable Reformulationscited by 291
  9. 2013Optimization, Learning, and Games with Predictable Sequencescited by 188
  10. 2019Distributionally Robust Language Modelingcited by 143
  11. 2018Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Banditscited by 124
  12. 2013Data-Driven Robust Optimizationcited by 85
12 more
  1. 2019Fairness risk measurescited by 85
  2. 2019Distributionally Robust Optimization and Generalization in Kernel Methodscited by 73
  3. 2020Coping with Label Shift via Distributionally Robust Optimisationcited by 70
  4. 2020Distributionally Robust Bayesian Optimizationcited by 61
  5. 2020An Online Method for A Class of Distributionally Robust Optimization with Non-Convex Objectivescited by 42
  6. 2019Adaptive Sampling for Stochastic Risk-Averse Learningcited by 39
  7. 2021Non-convex Distributionally Robust Optimization: Non-asymptotic Analysiscited by 39
  8. 2022On-Demand Sampling: Learning Optimally from Multiple Distributionscited by 39
  9. 2021Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Losscited by 17
  10. 2021Predict then Interpolate: A Simple Algorithm to Learn Stable Classifierscited by 16
  11. 2018Distributionally Robust Submodular Maximizationcited by 12
  12. 2021Lexicographically Fair Learning: Algorithms and Generalizationcited by 4

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 5; 2024: 3; 2025: 4; 2026: 5.

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  1. 2026Group Distributionally Robust Optimization-Driven Reinforcement Learning for LLM Reasoningcited by 12
  2. 2024Efficient Algorithms for Empirical Group Distributionally Robust Optimization and Beyondcited by 11
  3. 2023Using Early Readouts to Mediate Featural Bias in Distillationcited by 7
  4. 2024Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsitycited by 5
  5. 2023Stochastic Approximation Approaches to Group Distributionally Robust Optimization and Beyondcited by 4
  6. 2023Efficient Stochastic Approximation of Minimax Excess Risk Optimizationcited by 4
  7. 2023Distributionally Robust Learning for Multi-source Unsupervised Domain Adaptationcited by 4
  8. 2023A Near-Optimal Single-Loop Stochastic Algorithm for Convex Finite-Sum Coupled Compositional Optimizationcited by 3
  9. 2024Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometrycited by 2
  10. 2025Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mappingcited by 2
  11. 2025Group Distributionally Robust Optimization with Flexible Sample Queriescited by 2
  12. 2025Group Distributionally Robust Machine Learning under Group Level Distributional Uncertaintycited by 2
5 more
  1. 2025FAST-CAD: A Fairness-Aware Framework for Non-Contact Stroke Diagnosiscited by 2
  2. 2026Is Multi-Distribution Learning as Easy as PAC Learning: Sharp Rates with Bounded Label Noisecited by 1
  3. 2026Distributionally Robust Federated Learning with Multi-Source Datacited by 0
  4. 2026Communication-Efficient Agnostic Federated Learning via Faster Convergence and Compressioncited by 0
  5. 2026Dynamic Minimax Regret Optimization for Robust LLM Post-Trainingcited by 0