default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDAlexey Kurakin
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[c17]Aldo G. Carranza, Rezsa Farahani, Natalia Ponomareva, Alexey Kurakin, Matthew Jagielski, Milad Nasr:
Synthetic Query Generation for Privacy-Preserving Deep Retrieval Systems using Differentially Private Language Models. NAACL-HLT 2024: 3920-3930- [i26]Yunjuan Wang, Hussein Hazimeh, Natalia Ponomareva, Alexey Kurakin, Ibrahim Hammoud, Raman Arora
:
DART: A Principled Approach to Adversarially Robust Unsupervised Domain Adaptation. CoRR abs/2402.11120 (2024) - [i25]Sanghyun Hong, Nicholas Carlini, Alexey Kurakin:
Diffusion Denoising as a Certified Defense against Clean-label Poisoning. CoRR abs/2403.11981 (2024) - [i24]Kareem Amin, Alex Bie, Weiwei Kong, Alexey Kurakin, Natalia Ponomareva, Umar Syed, Andreas Terzis, Sergei Vassilvitskii:
Private prediction for large-scale synthetic text generation. CoRR abs/2407.12108 (2024) - 2023
- [j3]Natalia Ponomareva, Hussein Hazimeh, Alex Kurakin, Zheng Xu, Carson Denison, H. Brendan McMahan, Sergei Vassilvitskii, Steve Chien, Abhradeep Guha Thakurta:
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy. J. Artif. Intell. Res. 77: 1113-1201 (2023) - [j2]Harsh Mehta, Walid Krichene, Abhradeep Guha Thakurta, Alexey Kurakin, Ashok Cutkosky:
Differentially Private Image Classification from Features. Trans. Mach. Learn. Res. 2023 (2023) - [j1]Harsh Mehta, Abhradeep Guha Thakurta, Alexey Kurakin, Ashok Cutkosky:
Towards Large Scale Transfer Learning for Differentially Private Image Classification. Trans. Mach. Learn. Res. 2023 (2023) - [c16]Natalia Ponomareva, Sergei Vassilvitskii, Zheng Xu, Brendan McMahan, Alexey Kurakin, Chiyaun Zhang:
How to DP-fy ML: A Practical Tutorial to Machine Learning with Differential Privacy. KDD 2023: 5823-5824 - [c15]Elie Bursztein, Marina Zhang, Owen Vallis, Xinyu Jia, Alexey Kurakin:
RETVec: Resilient and Efficient Text Vectorizer. NeurIPS 2023 - [c14]Sanghyun Hong, Nicholas Carlini, Alexey Kurakin:
Publishing Efficient On-device Models Increases Adversarial Vulnerability. SaTML 2023: 271-290 - [i23]Elie Bursztein, Marina Zhang, Owen Vallis, Xinyu Jia, Alexey Kurakin:
RetVec: Resilient and Efficient Text Vectorizer. CoRR abs/2302.09207 (2023) - [i22]Natalia Ponomareva, Hussein Hazimeh, Alex Kurakin, Zheng Xu, Carson Denison, H. Brendan McMahan, Sergei Vassilvitskii, Steve Chien, Abhradeep Thakurta:
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy. CoRR abs/2303.00654 (2023) - [i21]Aldo Gael Carranza, Rezsa Farahani, Natalia Ponomareva, Alex Kurakin, Matthew Jagielski, Milad Nasr:
Privacy-Preserving Recommender Systems with Synthetic Query Generation using Differentially Private Large Language Models. CoRR abs/2305.05973 (2023) - [i20]Alexey Kurakin, Natalia Ponomareva, Umar Syed, Liam MacDermed, Andreas Terzis:
Harnessing large-language models to generate private synthetic text. CoRR abs/2306.01684 (2023) - 2022
- [c13]David Berthelot, Rebecca Roelofs, Kihyuk Sohn, Nicholas Carlini, Alexey Kurakin:
AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation. ICLR 2022 - [c12]Sanghyun Hong, Nicholas Carlini, Alexey Kurakin:
Handcrafted Backdoors in Deep Neural Networks. NeurIPS 2022 - [i19]Alexey Kurakin, Steve Chien, Shuang Song, Roxana Geambasu, Andreas Terzis, Abhradeep Thakurta:
Toward Training at ImageNet Scale with Differential Privacy. CoRR abs/2201.12328 (2022) - [i18]Harsh Mehta, Abhradeep Thakurta, Alexey Kurakin, Ashok Cutkosky:
Large Scale Transfer Learning for Differentially Private Image Classification. CoRR abs/2205.02973 (2022) - [i17]Harsh Mehta, Walid Krichene, Abhradeep Thakurta, Alexey Kurakin, Ashok Cutkosky:
Differentially Private Image Classification from Features. CoRR abs/2211.13403 (2022) - [i16]Sanghyun Hong, Nicholas Carlini, Alexey Kurakin:
Publishing Efficient On-device Models Increases Adversarial Vulnerability. CoRR abs/2212.13700 (2022) - 2021
- [i15]Sanghyun Hong, Nicholas Carlini, Alexey Kurakin:
Handcrafted Backdoors in Deep Neural Networks. CoRR abs/2106.04690 (2021) - [i14]David Berthelot, Rebecca Roelofs, Kihyuk Sohn, Nicholas Carlini, Alex Kurakin:
AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation. CoRR abs/2106.04732 (2021) - 2020
- [c11]David Berthelot, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Kihyuk Sohn, Han Zhang, Colin Raffel:
ReMixMatch: Semi-Supervised Learning with Distribution Matching and Augmentation Anchoring. ICLR 2020 - [c10]Sumanth Dathathri, Krishnamurthy Dvijotham, Alexey Kurakin, Aditi Raghunathan, Jonathan Uesato, Rudy Bunel, Shreya Shankar, Jacob Steinhardt, Ian J. Goodfellow, Percy Liang, Pushmeet Kohli:
Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming. NeurIPS 2020 - [c9]Kihyuk Sohn, David Berthelot, Nicholas Carlini, Zizhao Zhang, Han Zhang, Colin Raffel, Ekin Dogus Cubuk, Alexey Kurakin, Chun-Liang Li:
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence. NeurIPS 2020 - [c8]Matthew Jagielski, Nicholas Carlini, David Berthelot, Alex Kurakin, Nicolas Papernot:
High Accuracy and High Fidelity Extraction of Neural Networks. USENIX Security Symposium 2020: 1345-1362 - [i13]Kihyuk Sohn, David Berthelot, Chun-Liang Li, Zizhao Zhang, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Han Zhang, Colin Raffel:
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence. CoRR abs/2001.07685 (2020) - [i12]Sumanth Dathathri, Krishnamurthy Dvijotham, Alexey Kurakin, Aditi Raghunathan, Jonathan Uesato, Rudy Bunel, Shreya Shankar, Jacob Steinhardt, Ian J. Goodfellow, Percy Liang, Pushmeet Kohli:
Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming. CoRR abs/2010.11645 (2020)
2010 – 2019
- 2019
- [i11]Nicholas Carlini, Anish Athalye, Nicolas Papernot, Wieland Brendel, Jonas Rauber, Dimitris Tsipras, Ian J. Goodfellow, Aleksander Madry, Alexey Kurakin:
On Evaluating Adversarial Robustness. CoRR abs/1902.06705 (2019) - [i10]Matthew Jagielski, Nicholas Carlini, David Berthelot, Alex Kurakin, Nicolas Papernot:
High-Fidelity Extraction of Neural Network Models. CoRR abs/1909.01838 (2019) - [i9]David Berthelot, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Kihyuk Sohn, Han Zhang, Colin Raffel:
ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring. CoRR abs/1911.09785 (2019) - 2018
- [c7]Florian Tramèr, Alexey Kurakin, Nicolas Papernot, Ian J. Goodfellow, Dan Boneh, Patrick D. McDaniel:
Ensemble Adversarial Training: Attacks and Defenses. ICLR (Poster) 2018 - [c6]Gamaleldin F. Elsayed, Shreya Shankar, Brian Cheung, Nicolas Papernot, Alexey Kurakin, Ian J. Goodfellow, Jascha Sohl-Dickstein:
Adversarial Examples that Fool both Computer Vision and Time-Limited Humans. NeurIPS 2018: 3914-3924 - [i8]Gamaleldin F. Elsayed, Shreya Shankar, Brian Cheung, Nicolas Papernot, Alex Kurakin, Ian J. Goodfellow, Jascha Sohl-Dickstein:
Adversarial Examples that Fool both Human and Computer Vision. CoRR abs/1802.08195 (2018) - [i7]Harini Kannan, Alexey Kurakin, Ian J. Goodfellow:
Adversarial Logit Pairing. CoRR abs/1803.06373 (2018) - [i6]Alexey Kurakin, Ian J. Goodfellow, Samy Bengio, Yinpeng Dong, Fangzhou Liao, Ming Liang, Tianyu Pang, Jun Zhu, Xiaolin Hu, Cihang Xie, Jianyu Wang, Zhishuai Zhang, Zhou Ren, Alan L. Yuille, Sangxia Huang, Yao Zhao, Yuzhe Zhao, Zhonglin Han, Junjiajia Long, Yerkebulan Berdibekov, Takuya Akiba, Seiya Tokui, Motoki Abe:
Adversarial Attacks and Defences Competition. CoRR abs/1804.00097 (2018) - [i5]Wieland Brendel, Jonas Rauber, Alexey Kurakin, Nicolas Papernot, Behar Veliqi, Marcel Salathé, Sharada P. Mohanty, Matthias Bethge:
Adversarial Vision Challenge. CoRR abs/1808.01976 (2018) - 2017
- [c5]Alexey Kurakin, Ian J. Goodfellow, Samy Bengio:
Adversarial Machine Learning at Scale. ICLR (Poster) 2017 - [c4]Alexey Kurakin, Ian J. Goodfellow, Samy Bengio:
Adversarial examples in the physical world. ICLR (Workshop) 2017 - [c3]Esteban Real, Sherry Moore, Andrew Selle, Saurabh Saxena, Yutaka I. Leon-Suematsu, Jie Tan, Quoc V. Le, Alexey Kurakin:
Large-Scale Evolution of Image Classifiers. ICML 2017: 2902-2911 - [i4]Esteban Real, Sherry Moore, Andrew Selle, Saurabh Saxena, Yutaka I. Leon-Suematsu, Quoc V. Le, Alex Kurakin:
Large-Scale Evolution of Image Classifiers. CoRR abs/1703.01041 (2017) - [i3]Florian Tramèr, Alexey Kurakin, Nicolas Papernot, Dan Boneh, Patrick D. McDaniel:
Ensemble Adversarial Training: Attacks and Defenses. CoRR abs/1705.07204 (2017) - 2016
- [i2]Alexey Kurakin, Ian J. Goodfellow, Samy Bengio:
Adversarial examples in the physical world. CoRR abs/1607.02533 (2016) - [i1]Alexey Kurakin, Ian J. Goodfellow, Samy Bengio:
Adversarial Machine Learning at Scale. CoRR abs/1611.01236 (2016) - 2011
- [c2]Leonid M. Mestetskiy, Irina Bakina, Alexey Kurakin:
Hand Geometry Analysis by Continuous Skeletons. ICIAR (2) 2011: 130-139 - [c1]Alexey Kurakin, Leonid M. Mestetskiy:
Hand Gesture Recognition through On-line Skeletonization - Application of Continuous Skeleton to Real-time Shape Analysis. VISAPP 2011: 555-560
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 22:21 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
