Cover Image

From Distributional Robustness to Robust Statistics: A Confidence Sets Perspective

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chan, Gabriel, Van Parys, Bart, Bennouna, Amine
Format:	Preprint
Published:	2024
Subjects:	Optimization and Control Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning and Decision-Making with Data: Optimal Formulations and Phase Transitions
by: Bennouna, Amine, et al.
Published: (2021)

Holistic Robust Data-Driven Decisions
by: Bennouna, Amine, et al.
Published: (2022)

What Data Enables Optimal Decisions? An Exact Characterization for Linear Optimization
by: Bennouna, Omar, et al.
Published: (2025)

Learning Decision-Focused Uncertainty Sets in Robust Optimization
by: Wang, Irina, et al.
Published: (2023)

Globalized Adversarial Regret Optimization: Robust Decisions with Uncalibrated Predictions
by: Kurtz, Jannis, et al.
Published: (2026)

Mean Robust Optimization
by: Wang, Irina, et al.
Published: (2022)

Efficient Data-Driven Optimization with Noisy Data
by: Van Parys, Bart P. G.
Published: (2021)

Stochastic Optimization with Optimal Importance Sampling
by: Aolaritei, Liviu, et al.
Published: (2025)

Data Informativeness in Linear Optimization under Uncertainty
by: Bennouna, Omar, et al.
Published: (2026)

Statistical Properties of Robust Satisficing
by: Li, Zhiyi, et al.
Published: (2024)

Distributionally Robust Regret Optimal Control Under Moment-Based Ambiguity Sets
by: Taha, Feras Al, et al.
Published: (2025)

A Geometric Unification of Distributionally Robust Covariance Estimators: Shrinking the Spectrum by Inflating the Ambiguity Set
by: Yue, Man-Chung, et al.
Published: (2024)

Decision Making under the Exponential Family: Distributionally Robust Optimisation with Bayesian Ambiguity Sets
by: Dellaporta, Charita, et al.
Published: (2024)

Distributionally Robust Optimization
by: Kuhn, Daniel, et al.
Published: (2024)

Nonlinear Distributionally Robust Optimization
by: Sheriff, Mohammed Rayyan, et al.
Published: (2023)

Distributionally-Robust Learning to Optimize
by: Ranjan, Vinit, et al.
Published: (2026)

Sinkhorn Distributionally Robust Optimization
by: Wang, Jie, et al.
Published: (2021)

Wasserstein Distributionally Robust Regret Optimization
by: Fiechtner, Lukas-Benedikt, et al.
Published: (2025)

Distributionally Robust Learning in Survival Analysis
by: Jin, Yeping, et al.
Published: (2025)

Distributionally Robust Multi-Objective Optimization
by: Yang, Yufeng, et al.
Published: (2026)

Wasserstein Distributionally Robust Online Learning
by: Chen, Guixian, et al.
Published: (2026)

Robust Out-of-Distribution Stochastic Optimization
by: Li, Xianyu, et al.
Published: (2026)

Robust Sublinear Convergence Rates for Iterative Bregman Projections
by: Peyré, Gabriel
Published: (2026)

On the Foundation of Distributionally Robust Reinforcement Learning
by: Wang, Shengbo, et al.
Published: (2023)

Distributionally Robust Federated Learning with Outlier Resilience
by: Wang, Zifan, et al.
Published: (2025)

Non-Convex Robust Hypothesis Testing using Sinkhorn Uncertainty Sets
by: Wang, Jie, et al.
Published: (2024)

Efficient Algorithms for Robust Markov Decision Processes with $s$-Rectangular Ambiguity Sets
by: Ho, Chin Pang, et al.
Published: (2026)

Wasserstein Distributionally Robust Shallow Convex Neural Networks
by: Pallage, Julien, et al.
Published: (2024)

Group Distributionally Robust Optimization with Flexible Sample Queries
by: Bai, Haomin, et al.
Published: (2025)

Mixed-feature Logistic Regression Robust to Distribution Shifts
by: Sun, Qingshi, et al.
Published: (2025)

Learning Optimal Classification Trees Robust to Distribution Shifts
by: Justin, Nathan, et al.
Published: (2023)

On Generalization and Regularization via Wasserstein Distributionally Robust Optimization
by: Wu, Qinyu, et al.
Published: (2022)

Subgradient Methods for Nonsmooth Convex Functions with Adversarial Errors
by: Gösgens, Martijn, et al.
Published: (2025)

Sparse Classification: a scalable discrete optimization perspective
by: Bertsimas, Dimitris, et al.
Published: (2017)

Statistical Robustness of Interval CVaR Based Regression Models under Perturbation and Contamination
by: You, Yulei, et al.
Published: (2026)

Sample Complexity of Variance-reduced Distributionally Robust Q-learning
by: Wang, Shengbo, et al.
Published: (2023)

Near-Optimal Algorithms for Group Distributionally Robust Optimization and Beyond
by: Soma, Tasuku, et al.
Published: (2022)

Enhancing Distributional Robustness in Principal Component Analysis by Wasserstein Distances
by: Wang, Lei, et al.
Published: (2025)

Sample Complexity of Distributionally Robust Average-Reward Reinforcement Learning
by: Chen, Zijun, et al.
Published: (2025)

Unifying Distributionally Robust Optimization via Optimal Transport Theory
by: Blanchet, Jose, et al.
Published: (2023)