Cullina, Daniel

8 publications

ICMLW 2023 A Theoretical Perspective on the Robustness of Feature Extractors Arjun Nitin Bhagoji, Daniel Cullina, Ben Y. Zhao

NeurIPS 2023 Characterizing the Optimal $0-1$ Loss for Multi-Class Classification with a Test-Time Attacker Sihui Dai, Wenxin Ding, Arjun Nitin Bhagoji, Daniel Cullina, Heather Zheng, Ben Zhao, Prateek Mittal

ICMLW 2023 Characterizing the Optimal $0-1$ Loss for Multi-Class Classification with a Test-Time Attacker Sihui Dai, Wenxin Ding, Arjun Nitin Bhagoji, Daniel Cullina, Ben Y. Zhao, Haitao Zheng, Prateek Mittal

NeurIPSW 2022 Lower Bounds on 0-1 Loss for Multi-Class Classification with a Test-Time Attacker Sihui Dai, Wenxin Ding, Arjun Nitin Bhagoji, Daniel Cullina, Prateek Mittal, Ben Y. Zhao

ICML 2021 Lower Bounds on Cross-Entropy Loss in the Presence of Test-Time Adversaries Arjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag, Prateek Mittal

AISTATS 2019 Database Alignment with Gaussian Features Osman E. Dai, Daniel Cullina, Negar Kiyavash

NeurIPS 2019 Lower Bounds on Adversarial Robustness from Optimal Transport Arjun Nitin Bhagoji, Daniel Cullina, Prateek Mittal

NeurIPS 2018 PAC-Learning in the Presence of Adversaries Daniel Cullina, Arjun Nitin Bhagoji, Prateek Mittal