distributionally robust optimization

Bayesian Nonparametrics Meets Data-Driven Distributionally Robust Optimization NeurIPS 2024 Credal Deep Ensembles for Uncertainty Quantification NeurIPS 2024 Differentiable Distributionally Robust Optimization Layers ICML 2024 Distributionally Generative Augmentation for Fair Facial Attribute Classification CVPR 2024 Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity JMLR 2024 Distributionally Robust Model-based Reinforcement Learning with Large State Spaces AISTATS 2024 Distributionally Robust Off-Dynamics Reinforcement Learning: Provable Efficiency with Linear Function Approximation AISTATS 2024 Distributionally Robust Optimization as a Scalable Framework to Characterize Extreme Value Distributions UAI 2024 Distributionally Robust Optimization with Bias and Variance Reduction ICLR 2024 Distributionally Robust Performative Prediction NeurIPS 2024 Distributionally Robust Quickest Change Detection using Wasserstein Uncertainty Sets AISTATS 2024 Doubly Robust Instance-Reweighted Adversarial Training ICLR 2024 Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization NeurIPS 2024 Fairness in Survival Analysis with Distributionally Robust Optimization JMLR 2024 Fast, blind, and accurate: Tuning-free sparse regression with global linear convergence COLT 2024 f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization ICLR 2024 Gradual Domain Adaptation via Manifold-Constrained Distributionally Robust Optimization NeurIPS 2024 Label-Efficient Group Robustness via Out-of-Distribution Concept Curation CVPR 2024 Large-Scale Non-convex Stochastic Constrained Distributionally Robust Optimization AAAI 2024 Learning from Noisy Labels via Conditional Distributionally Robust Optimization NeurIPS 2024 Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning NeurIPS 2024 Mitigating Reward Overoptimization via Lightweight Uncertainty Estimation NeurIPS 2024 On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity ICML 2024 On the Fairness ROAD: Robust Optimization for Adversarial Debiasing ICLR 2024 On the Inductive Biases of Demographic Parity-based Fair Learning Algorithms UAI 2024