Squillante, Mark

5 publications

NeurIPS 2022 A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization Songtao Lu, Siliang Zeng, Xiaodong Cui, Mark Squillante, Lior Horesh, Brian Kingsbury, Jia Liu, Mingyi Hong

NeurIPS 2021 Efficient Generalization with Distributionally Robust Learning Soumyadip Ghosh, Mark Squillante, Ebisa Wollega

NeurIPS 2020 Quantifying the Empirical Wasserstein Distance to a Set of Measures: Beating the Curse of Dimensionality Nian Si, Jose Blanchet, Soumyadip Ghosh, Mark Squillante

NeurIPS 2019 A Family of Robust Stochastic Operators for Reinforcement Learning Yingdong Lu, Mark Squillante, Chai Wah Wu

ICML 2019 PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach Lily Weng, Pin-Yu Chen, Lam Nguyen, Mark Squillante, Akhilan Boopathy, Ivan Oseledets, Luca Daniel