Florian Tramèr

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	All	Since 2018
Citations	13556	13259
h-index	36	35
i10-index	43	43

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Nicholas CarliniGoogle BrainVerified email at google.com
Dan BonehProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Nicolas PapernotUniversity of Toronto and Vector InstituteVerified email at utoronto.ca
Ari JuelsProfessor, Computer Science, Cornell Tech (Jacobs); Co-Director, IC3Verified email at cornell.edu
Matthew JagielskiGoogle ResearchVerified email at google.com
Ian GoodfellowDeepMindVerified email at deepmind.com
Jean-Pierre HubauxProfessor, EPFLVerified email at epfl.ch
Fan ZhangYale UniversityVerified email at yale.edu
Katherine LeeResearcher, Google Brain ResearchVerified email at google.com
Alexey KurakinResearch Software Engineer, Google BrainVerified email at google.com
Patrick McDanielWilliam L. Weiss Professor, Computer Science and Engineering, Penn State UnviersityVerified email at cse.psu.edu
Wieland BrendelResearch Group Leader, Max Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Dawn SongProfessor of Computer Science, UC BerkeleyVerified email at cs.berkeley.edu
Thomas RistenpartAssociate Professor of Computer Science, Cornell TechVerified email at cornell.edu
Aleksander MądryMITVerified email at mit.edu
Colin RaffelUNC Chapel Hill and Hugging FaceVerified email at cs.unc.edu
huang linShanghai Jiao Tong University/University of floridaVerified email at ufl.edu
Michael ReiterJames B. Duke Distinguished Professor, Duke UniversityVerified email at duke.edu
Giancarlo PellegrinoCISPA Helmholtz Center for Information SecurityVerified email at cispa.de
Eric WallaceUC BerkeleyVerified email at berkeley.edu

Florian Tramèr

Assistant Professor of Computer Science, ETH Zurich

Verified email at inf.ethz.ch - Homepage

ML Security Computer Security Cryptography Privacy


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Advances and open problems in federated learning P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ... Foundations and Trends® in Machine Learning 14 (1), 2019	3078	2019
Ensemble Adversarial Training: Attacks and Defenses F Tramèr, A Kurakin, N Papernot, I Goodfellow, D Boneh, P McDaniel International Conference on Learning Representations (ICLR), 2018	2377	2018
Stealing Machine Learning Models via Prediction APIs F Tramèr, F Zhang, A Juels, MK Reiter, T Ristenpart 25th USENIX security symposium (USENIX Security 16), 601-618, 2016	1558	2016
On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021	833	2021
On evaluating adversarial robustness N Carlini, A Athalye, N Papernot, W Brendel, J Rauber, D Tsipras, ... arXiv preprint arXiv:1902.06705, 2019	690	2019
On adaptive attacks to adversarial example defenses F Tramèr, N Carlini, W Brendel, A Madry Conference on Neural Information Processing Systems (NeurIPS) 33, 2020	553	2020
The space of transferable adversarial examples F Tramèr, N Papernot, I Goodfellow, D Boneh, P McDaniel arXiv preprint arXiv:1704.03453, 2017	509	2017
Extracting Training Data from Large Language Models N Carlini, F Tramèr, E Wallace, M Jagielski, A Herbert-Voss, K Lee, ... 30th USENIX Security Symposium (USENIX Security 21), 2633--2650, 2021	507	2021
Physical adversarial examples for object detectors K Eykholt, I Evtimov, E Fernandes, B Li, A Rahmati, F Tramèr, A Prakash, ... 12th USENIX Workshop on Offensive Technologies (WOOT 18), 2018	353	2018
Slalom: Fast, verifiable and private execution of neural networks in trusted hardware F Tramèr, D Boneh International Conference on Learning Representations (ICLR), 2019	302	2019
Adversarial training and robustness for multiple perturbations F Tramèr, D Boneh Conference on Neural Information Processing Systems (NeurIPS) 32, 2019	286	2019
Label-Only Membership Inference Attacks CAC Choo, F Tramèr, N Carlini, N Papernot International Conference on Machine Learning (ICML), 1964--1974, 2021	190*	2021
Fairtest: Discovering unwarranted associations in data-driven applications F Tramer, V Atlidakis, R Geambasu, D Hsu, JP Hubaux, M Humbert, ... IEEE European Symposium on Security and Privacy (EuroS&P), 401-416, 2017	180*	2017
Sentinet: Detecting localized universal attacks against deep learning systems E Chou, F Tramèr, G Pellegrino IEEE Security and Privacy Workshops (SPW), 48-54, 2020	170*	2020
Advances and open problems in federated learning P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ... arXiv preprint arXiv:1912.04977, 0	127*
Differentially Private Learning Needs Better Features (or Much More Data) F Tramèr, D Boneh International Conference on Learning Representations (ICLR), 2021	119	2021
Sealed-glass proofs: Using transparent enclaves to prove and sell knowledge F Tramèr, F Zhang, H Lin, JP Hubaux, A Juels, E Shi IEEE European Symposium on Security and Privacy (EuroS&P), 19-34, 2017	112	2017
Fundamental tradeoffs between invariance and sensitivity to adversarial perturbations F Tramèr, J Behrmann, N Carlini, N Papernot, JH Jacobsen International Conference on Machine Learning (ICML), 9561-9571, 2020	104*	2020
Formal abstractions for attested execution secure processors R Pass, E Shi, F Tramèr Annual International Conference on the Theory and Applications of …, 2017	103	2017
Differential privacy with bounded priors: reconciling utility and privacy in genome-wide association studies F Tramèr, Z Huang, JP Hubaux, E Ayday 22nd ACM SIGSAC Conference on Computer and Communications Security (CCS …, 2015	102	2015

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