Kurakin, Alexey

12 publications

TMLR 2023 Differentially Private Image Classification from Features Harsh Mehta, Walid Krichene, Abhradeep Guha Thakurta, Alexey Kurakin, Ashok Cutkosky

NeurIPS 2023 RETVec: Resilient and Efficient Text Vectorizer Elie Bursztein, Marina Zhang, Owen Vallis, Xinyu Jia, Alexey Kurakin

TMLR 2023 Towards Large Scale Transfer Learning for Differentially Private Image Classification Harsh Mehta, Abhradeep Guha Thakurta, Alexey Kurakin, Ashok Cutkosky

ICLR 2022 AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation David Berthelot, Rebecca Roelofs, Kihyuk Sohn, Nicholas Carlini, Alexey Kurakin

NeurIPS 2022 Handcrafted Backdoors in Deep Neural Networks Sanghyun Hong, Nicholas Carlini, Alexey Kurakin

NeurIPS 2020 Enabling Certification of Verification-Agnostic Networks via Memory-Efficient Semidefinite Programming Sumanth Dathathri, Krishnamurthy Dvijotham, Alexey Kurakin, Aditi Raghunathan, Jonathan Uesato, Rudy R Bunel, Shreya Shankar, Jacob Steinhardt, Ian Goodfellow, Percy Liang, Pushmeet Kohli

NeurIPS 2020 FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence Kihyuk Sohn, David Berthelot, Nicholas Carlini, Zizhao Zhang, Han Zhang, Colin A Raffel, Ekin Dogus Cubuk, Alexey Kurakin, Chun-Liang Li

NeurIPS 2018 Adversarial Examples That Fool Both Computer Vision and Time-Limited Humans Gamaleldin Elsayed, Shreya Shankar, Brian Cheung, Nicolas Papernot, Alexey Kurakin, Ian Goodfellow, Jascha Sohl-Dickstein

ICLR 2018 Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr, Alexey Kurakin, Nicolas Papernot, Ian Goodfellow, Dan Boneh, Patrick McDaniel

ICLR 2017 Adversarial Examples in the Physical World Alexey Kurakin, Ian J. Goodfellow, Samy Bengio

ICLR 2017 Adversarial Machine Learning at Scale Alexey Kurakin, Ian J. Goodfellow, Samy Bengio

ICML 2017 Large-Scale Evolution of Image Classifiers Esteban Real, Sherry Moore, Andrew Selle, Saurabh Saxena, Yutaka Leon Suematsu, Jie Tan, Quoc V. Le, Alexey Kurakin