{"total":35,"rows":[{"id":"2201.08956","title":"The Many Faces of Adversarial Risk","created":"2022-01-22","cited_by_count":28,"area":null},{"id":"2112.01694","title":"On the Existence of the Adversarial Bayes Classifier (Extended Version)","created":"2021-12-03","cited_by_count":25,"area":null},{"id":"2102.06905","title":"Mixed Nash Equilibria in the Adversarial Examples Game","created":"2021-02-13","cited_by_count":22,"area":null},{"id":"2204.12676","title":"The Multimarginal Optimal Transport Formulation of Adversarial Multiclass Classification","created":"2022-04-27","cited_by_count":21,"area":null},{"id":"2111.13613","title":"The Geometry of Adversarial Training in Binary Classification","created":"2021-11-26","cited_by_count":20,"area":null},{"id":"2206.09098","title":"Existence and Minimax Theorems for Adversarial Surrogate Risks in Binary Classification","created":"2022-06-18","cited_by_count":15,"area":null},{"id":"2101.06309","title":"Fundamental Tradeoffs in Distributionally Adversarial Training","created":"2021-01-15","cited_by_count":12,"area":null},{"id":"2205.10022","title":"Towards Consistency in Adversarial Classification","created":"2022-05-20","cited_by_count":12,"area":null},{"id":"2309.16096","title":"Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness","created":"2023-09-28","cited_by_count":11,"area":null},{"id":"2103.09947","title":"Understanding Generalization in Adversarial Training via the Bias-Variance Decomposition","created":"2021-03-17","cited_by_count":10,"area":null},{"id":"2211.15223","title":"Gamma-convergence of a nonlocal perimeter arising in adversarial machine learning","created":"2022-11-28","cited_by_count":10,"area":null},{"id":"2301.13375","title":"Optimal Transport Perturbations for Safe Reinforcement Learning with Robustness Guarantees","created":"2023-01-31","cited_by_count":9,"area":null},{"id":"2303.09767","title":"It Is All About Data: A Survey on the Effects of Data on Adversarial Robustness","created":"2023-03-17","cited_by_count":9,"area":null},{"id":"2305.00075","title":"On the existence of solutions to adversarial training in multiclass classification","created":"2023-04-28","cited_by_count":9,"area":null},{"id":"2110.11950","title":"Adversarial robustness for latent models: Revisiting the robust-standard accuracies tradeoff","created":"2021-10-22","cited_by_count":8,"area":null},{"id":"2302.10722","title":"Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker","created":"2023-02-21","cited_by_count":6,"area":null},{"id":"2104.02189","title":"Robust Classification Under $\\ell_0$ Attack for the Gaussian Mixture Model","created":"2021-04-05","cited_by_count":5,"area":null},{"id":"2209.11539","title":"Quantile-constrained Wasserstein projections for robust interpretability of numerical and machine learning models","created":"2022-09-23","cited_by_count":4,"area":null},{"id":"2301.03662","title":"On adversarial robustness and the use of Wasserstein ascent-descent dynamics to enforce it","created":"2023-01-09","cited_by_count":4,"area":null},{"id":"2404.14402","title":"A mean curvature flow arising in adversarial training","created":"2024-04-22","cited_by_count":4,"area":null},{"id":"2103.05857","title":"Fast block-coordinate Frank-Wolfe algorithm for semi-relaxed optimal transport","created":"2021-03-10","cited_by_count":3,"area":null},{"id":"2404.16956","title":"A Notion of Uniqueness for the Adversarial Bayes Classifier","created":"2024-04-25","cited_by_count":3,"area":null},{"id":"2309.00771","title":"Non-Asymptotic Bounds for Adversarial Excess Risk under Misspecified Models","created":"2023-09-02","cited_by_count":2,"area":null},{"id":"2404.17358","title":"Adversarial Consistency and the Uniqueness of the Adversarial Bayes Classifier","created":"2024-04-26","cited_by_count":2,"area":null},{"id":"2410.09402","title":"Minimax rates of convergence for nonparametric regression under adversarial attacks","created":"2024-10-12","cited_by_count":2,"area":null},{"id":"2104.08382","title":"Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries","created":"2021-04-16","cited_by_count":1,"area":null},{"id":"2201.05274","title":"Eikonal depth: an optimal control approach to statistical depths","created":"2022-01-14","cited_by_count":1,"area":null},{"id":"2306.07544","title":"On Achieving Optimal Adversarial Test Error","created":"2023-06-13","cited_by_count":1,"area":null},{"id":"2406.14682","title":"Uniform Convergence of Adversarially Robust Classifiers","created":"2024-06-20","cited_by_count":1,"area":null},{"id":"2506.09348","title":"Adversarial Surrogate Risk Bounds for Binary Classification","created":"2025-06-11","cited_by_count":1,"area":null},{"id":"2112.02209","title":"Generalized Likelihood Ratio Test for Adversarially Robust Hypothesis Testing","created":"2021-12-04","cited_by_count":0,"area":null},{"id":"2205.15424","title":"Connecting adversarial attacks and optimal transport for domain adaptation","created":"2022-05-30","cited_by_count":0,"area":null},{"id":"2207.08137","title":"Achieve Optimal Adversarial Accuracy for Adversarial Deep Learning using Stackelberg Game","created":"2022-07-17","cited_by_count":0,"area":null},{"id":"2605.25352","title":"Certified Robustness from Approximate Gaussian Mixture Structures in Pretrained Latent Spaces","created":"2026-05-25","cited_by_count":0,"area":null},{"id":"2609.22240","title":"Statistical Inference for Adversarial Training: Central Limit Theorems via Optimal Transport","created":"2026-09-04","cited_by_count":0,"area":null}],"next_cursor":null}