Florian Tramèr

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	All	Since 2017
Citations	11573	11497
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
Ian GoodfellowDeepMindVerified email at deepmind.com
Matthew JagielskiGoogle ResearchVerified email at google.com
Jean-Pierre HubauxProfessor, EPFLVerified email at epfl.ch
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
Fan ZhangYale UniversityVerified email at yale.edu
Katherine LeeResearcher, Google Brain ResearchVerified email at google.com
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
Aleksander MądryMITVerified email at mit.edu
Giancarlo PellegrinoCISPA Helmholtz Center for Information SecurityVerified email at cispa.de
huang linShanghai Jiao Tong University/University of floridaVerified email at ufl.edu
Colin RaffelUNC Chapel Hill and Hugging FaceVerified email at cs.unc.edu
Atul PrakashProfessor of EECS, University of MichiganVerified email at umich.edu
Thomas RistenpartAssociate Professor of Computer Science, Cornell TechVerified email at cornell.edu
Michael ReiterJames B. Duke Distinguished Professor, Duke UniversityVerified email at duke.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	2523	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	2241	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	1387	2016
On evaluating adversarial robustness N Carlini, A Athalye, N Papernot, W Brendel, J Rauber, D Tsipras, ... arXiv preprint arXiv:1902.06705, 2019	635	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	497	2020
The space of transferable adversarial examples F Tramèr, N Papernot, I Goodfellow, D Boneh, P McDaniel arXiv preprint arXiv:1704.03453, 2017	488	2017
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	439	2021
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	402	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	321	2018
Slalom: Fast, verifiable and private execution of neural networks in trusted hardware F Tramèr, D Boneh International Conference on Learning Representations (ICLR), 2019	273	2019
Adversarial training and robustness for multiple perturbations F Tramèr, D Boneh Conference on Neural Information Processing Systems (NeurIPS) 32, 2019	257	2019
Label-Only Membership Inference Attacks CAC Choo, F Tramèr, N Carlini, N Papernot International Conference on Machine Learning (ICML), 1964--1974, 2021	148*	2021
Sentinet: Detecting localized universal attacks against deep learning systems E Chou, F Tramèr, G Pellegrino IEEE Security and Privacy Workshops (SPW), 48-54, 2020	146*	2020
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	138	2017
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	108*
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	105	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	101	2015
Differentially Private Learning Needs Better Features (or Much More Data) F Tramèr, D Boneh International Conference on Learning Representations (ICLR), 2021	99	2021
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	96*	2020
Formal abstractions for attested execution secure processors R Pass, E Shi, F Tramèr Annual International Conference on the Theory and Applications of …, 2017	96	2017

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