Bhagoji, Arjun Nitin

12 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

NeurIPS 2022 Finding Naturally Occurring Physical Backdoors in Image Datasets Emily Wenger, Roma Bhattacharjee, Arjun Nitin Bhagoji, Josephine Passananti, Emilio Andere, Heather Zheng, Ben Zhao

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

NeurIPS 2022 Understanding Robust Learning Through the Lens of Representation Similarities Christian Cianfarani, Arjun Nitin Bhagoji, Vikash Sehwag, Ben Zhao, Heather Zheng, Prateek Mittal

FnTML 2021 Advances and Open Problems in Federated Learning Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao

CVPR 2021 Backdoor Attacks Against Deep Learning Systems in the Physical World Emily Wenger, Josephine Passananti, Arjun Nitin Bhagoji, Yuanshun Yao, Haitao Zheng, 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

ICML 2019 Analyzing Federated Learning Through an Adversarial Lens Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal, Seraphin Calo

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