Alexey Kurakin

发表

Ensemble Adversarial Training: Attacks and Defenses pdf

Dan Boneh, Patrick McDaniel, Nicolas Papernot, 2017, ICLR.

Adversarial examples in the physical world pdf

Samy Bengio, Ian J. Goodfellow, Alexey Kurakin, 2016, ICLR.

FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence pdf

David Berthelot, Colin Raffel, Chun-Liang Li, 2020, NeurIPS.

Handcrafted Backdoors in Deep Neural Networks

Nicholas Carlini, A. Kurakin, Sanghyun Hong, 2021, NeurIPS.

Adversarial Machine Learning at Scale pdf

Samy Bengio, Ian J. Goodfellow, Alexey Kurakin, 2016, ICLR.

AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation

Nicholas Carlini, David Berthelot, Kihyuk Sohn, 2021, ICLR.

Large-Scale Evolution of Image Classifiers pdf

Quoc V. Le, Jie Tan, Saurabh Saxena, 2017, ICML.

Adversarial Vision Challenge pdf

Matthias Bethge, Marcel Salathé, Wieland Brendel, 2018, The NeurIPS '18 Competition.

Adversarial Examples that Fool both Human and Computer Vision pdf

Jascha Sohl-Dickstein, Brian Cheung, Nicolas Papernot, 2018, ArXiv.

Adversarial Examples that Fool both Computer Vision and Time-Limited Humans

Jascha Sohl-Dickstein, Brian Cheung, Nicolas Papernot, 2018, NeurIPS.

Technical Report on the CleverHans v2.1.0 Adversarial Examples Library

Ian J. Goodfellow, Tom B. Brown, Jonas Rauber, 2016, 1610.00768.

Toward Training at ImageNet Scale with Differential Privacy

Abhradeep Thakurta, A. Terzis, Roxana Geambasu, 2022, ArXiv.

On Evaluating Adversarial Robustness pdf

Aleksander Madry, Wieland Brendel, Nicholas Carlini, 2019, ArXiv.

Adversarial Logit Pairing pdf

Harini Kannan, Ian J. Goodfellow, Alexey Kurakin, 2018, NIPS 2018.

High Accuracy and High Fidelity Extraction of Neural Networks

Nicolas Papernot, Nicholas Carlini, David Berthelot, 2019, USENIX Security Symposium.

ReMixMatch: Semi-Supervised Learning with Distribution Matching and Augmentation Anchoring

David Berthelot, Colin Raffel, Han Zhang, 2020, ICLR.

Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming pdf

Ian Goodfellow, Pushmeet Kohli, Sumanth Dathathri, 2020, NeurIPS.

ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring

Nicholas Carlini, David Berthelot, Han Zhang, 2019, ArXiv.

Adversarial Attacks and Defences Competition pdf

Yao Zhao, Takuya Akiba, Motoki Abe, 2018, ArXiv.

Privacy-Preserving Recommender Systems with Synthetic Query Generation using Differentially Private Large Language Models

Aldo G. Carranza, Milad Nasr, N. Ponomareva, 2023, ArXiv.

Large Scale Transfer Learning for Differentially Private Image Classification

Abhradeep Thakurta, A. Kurakin, Harsh Mehta, 2022, Trans. Mach. Learn. Res..

How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy

H. B. McMahan, Abhradeep Thakurta, Zheng Xu, 2023, ArXiv.

High-Fidelity Extraction of Neural Network Models pdf

David Berthelot, Nicholas Carlini, Nicolas Papernot, 2019, ArXiv.

Harnessing large-language models to generate private synthetic text

Umar Syed, A. Terzis, Liam MacDermed, 2023, ArXiv.

Differentially Private Image Classification from Features

Abhradeep Thakurta, Walid Krichene, A. Kurakin, 2022, Trans. Mach. Learn. Res..

How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy

H. B. McMahan, Abhradeep Thakurta, Zheng Xu, 2023, J. Artif. Intell. Res..

Adversarial Forces of Physical Models

Ian J. Goodfellow, A. Madry, Jonas Rauber, 2020 .

A DA M ATCH : A U NIFIED A PPROACH TO S EMI S UPERVISED L EARNING AND D OMAIN A DAPTATION

Nicholas Carlini, Kihyuk Sohn, R. Roelofs, 2022 .

Adversarial examples influence human visual perception

Ian Goodfellow, Jascha Sohl-Dickstein, Brian Cheung, 2019, Journal of Vision.

RetVec: Resilient and Efficient Text Vectorizer

Elie Bursztein, Xinyu Jia, Owen Vallis, 2023, ArXiv.

Synthetic Query Generation for Privacy-Preserving Deep Retrieval Systems using Differentially Private Language Models

Aldo G. Carranza, Milad Nasr, N. Ponomareva, 2023, NAACL.

AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation

Nicholas Carlini, David Berthelot, Kihyuk Sohn, 2021, ICLR.

Diffusion Denoising as a Certified Defense against Clean-label Poisoning

Alexey Kurakin, Sanghyun Hong, Nicholas Carlini, 2024, ArXiv.