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Nicholas Carlini

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Generally, I am interested in developing attacks on machine learning systems; most of my work develops attacks demonstrating security and privacy risks of these systems. I have received best paper awards at ICML and IEEE S&P, and my work has been featured in the New York Times, the BBC, Nature Magazine, Science Magazine, Wired, and Popular Science.

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Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations

Tramèr Florian, Behrmann Jens,Carlini Nicholas,Papernot Nicolas, Jacobsen Jörn-Henrik

ICML, pp.9561-9571, (2020)

Cited by20EIBibtex

An Attack on InstaHide: Is Private Learning Possible with Instance Encoding

Nicholas Carlini, Samuel Deng,Sanjam Garg,Somesh Jha, Saeed Mahloujifar,Mohammad Mahmoody, Shuang Song,Abhradeep Thakurta,Florian Tramer

Bibtex

AISec'20: 13th Workshop on Artificial Intelligence and Security

Sadia Afroz,Nicholas Carlini, Ambra Demontis

CCS '20: 2020 ACM SIGSAC Conference on Computer and Communications Security Virtual Event ..., pp.2143-2144, (2020)

EIBibtex

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

David Berthelot,Nicholas Carlini,Ekin D. Cubuk,Alex Kurakin,Kihyuk Sohn,Han Zhang,Colin Raffel

ICLR, (2020)

Cited by60EIBibtex

Extracting Training Data from Large Language Models

Nicholas Carlini,Florian Tramer,Eric Wallace,Matthew Jagielski,Ariel Herbert-Voss,Katherine Lee, Adam Roberts,Tom Brown,Dawn Song, Ulfar Erlingsson,Alina Oprea,Colin Raffel

Bibtex

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, (2020)

EIBibtex

Erratum Concerning the Obfuscated Gradients Attack on Stochastic Activation Pruning

Guneet S. Dhillon,Nicholas Carlini

Bibtex

A Partial Break of the Honeypots Defense to Catch Adversarial Attacks

Nicholas Carlini

Bibtex

Label-Only Membership Inference Attacks

Christopher A. Choquette Choo,Florian Tramer,Nicholas Carlini,Nicolas Papernot

Cited by3Bibtex

Evading Deepfake-Image Detectors with White- and Black-Box Attacks

Nicholas Carlini, Hany Farid

CVPR Workshops, pp.2804-2813, (2020)

EIBibtex

Measuring Robustness to Natural Distribution Shifts in Image Classification

Rohan Taori,Achal Dave,Vaishaal Shankar,Nicholas Carlini,Benjamin Recht,Ludwig Schmidt

NeurIPS, (2020)

Cited by4EIBibtex

FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence

Sohn Kihyuk,Berthelot David,Li Chun-Liang,Zhang Zizhao,Carlini Nicholas,Cubuk Ekin D.,Kurakin Alex,Zhang Han,Raffel Colin

neural information processing systems, (2020)

Cited by75Bibtex

High Accuracy and High Fidelity Extraction of Neural Networks

Matthew Jagielski,Nicholas Carlini,David Berthelot,Alex Kurakin,Nicolas Papernot

USENIX Security Symposium, pp.1345-1362, (2020)

Cited by30EIBibtex

Cryptanalytic Extraction of Neural Network Models

Carlini Nicholas,Jagielski Matthew, Mironov Ilya

international cryptology conference, pp.189-218, (2020)

Cited by5Bibtex

On Adaptive Attacks to Adversarial Example Defenses

Tramer Florian,Carlini Nicholas,Brendel Wieland,Madry Aleksander

NeurIPS, (2020)

Cited by48EIBibtex

High-Fidelity Extraction of Neural Network Models

Jagielski Matthew,Carlini Nicholas,Berthelot David,Kurakin Alex,Papernot Nicolas

Cited by17Bibtex

MLSys: The New Frontier of Machine Learning Systems

Alexander Ratner,Dan Alistarh,Gustavo Alonso,David G Andersen,Peter Bailis, Sarah Bird,Nicholas Carlini,Bryan Catanzaro, Jennifer Chayes, Eric Chung, Bill Dally,Jeff Dean

arXiv preprint arXiv:1904.03257, (2019)

Cited by2Bibtex

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

Berthelot David,Carlini Nicholas,Cubuk Ekin D.,Kurakin Alex, Sohn Kihyuk,Zhang Han,Raffel Colin

Cited by61Bibtex

Distribution Density, Tails, and Outliers in Machine Learning: Metrics and Applications

Carlini Nicholas, Erlingsson Úlfar,Papernot Nicolas

Cited by7Bibtex

SysML: The New Frontier of Machine Learning Systems

Alexander Ratner,Dan Alistarh,Gustavo Alonso,Peter Bailis, Sarah Bird,Nicholas Carlini,Bryan Catanzaro, Eric Chung, Bill Dally,Jeff Dean,Inderjit S. Dhillon,Alexandros G. Dimakis

arXiv: Learning, (2019)

Cited by11EIBibtex

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