Saeed Mahloujifar

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Mohammad MahmoodyAssociate Professor, University of VirginiaDirección de correo verificada de virginia.edu
Prateek MittalProfessor, Princeton UniversityDirección de correo verificada de princeton.edu
Somesh JhaLubar Chair of Computer Science, University of WisconsinDirección de correo verificada de cs.wisc.edu
Dimitris DiochnosUniversity of Oklahoma, School of Computer ScienceDirección de correo verificada de math.uic.edu
Sanjam GargUniversity of California, BerkeleyDirección de correo verificada de berkeley.edu
Vikash SehwagPrinceton UniversityDirección de correo verificada de princeton.edu
Chong XiangPrinceton UniversityDirección de correo verificada de princeton.edu
Sihui DaiPhD student, Princeton UniversityDirección de correo verificada de princeton.edu
Abhradeep Guha ThakurtaGoogle Research - Brain TeamDirección de correo verificada de google.com
Nicholas CarliniGoogle BrainDirección de correo verificada de google.com
Florian TramèrAssistant Professor of Computer Science, ETH ZurichDirección de correo verificada de inf.ethz.ch
Xinyu TangPrinceton UniversityDirección de correo verificada de princeton.edu
David EvansUniversity of Virginia, Computer ScienceDirección de correo verificada de virginia.edu
Esha GhoshMicrosoft ResearchDirección de correo verificada de microsoft.com
Melissa ChaseMicrosoft ResearchDirección de correo verificada de microsoft.com
Tinashe HandinaCalifornia Institute of TechnologyDirección de correo verificada de caltech.edu
Mung ChiangPurdue UniversityDirección de correo verificada de purdue.edu
Milad NasrUniversity of Massachusetts AmherstDirección de correo verificada de cs.umass.edu
Amir HoumansadrUniversity of Massachusetts AmherstDirección de correo verificada de cs.umass.edu
virat shejwalkarPhD student, University of Massachusetts AmherstDirección de correo verificada de cs.umass.edu

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Saeed Mahloujifar

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Adversarial ML Privacy Cryptography Computational Complexity


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
The curse of concentration in robust learning: Evasion and poisoning attacks from concentration of measure S Mahloujifar, DI Diochnos, M Mahmoody Proceedings of the AAAI Conference on Artificial Intelligence 33, 4536-4543, 2019	134	2019
Improving adversarial robustness using proxy distributions V Sehwag, S Mahloujifar, T Handina, S Dai, C Xiang, M Chiang, P Mittal arXiv preprint arXiv:2104.09425 1, 2021	67*	2021
Adversarial risk and robustness: General definitions and implications for the uniform distribution D Diochnos, S Mahloujifar, M Mahmoody Advances in Neural Information Processing Systems 31, 2018	65	2018
Universal Multi-Party Poisoning Attacks S Mahloujifar, M Mahmoody, A Mohammed International Conference on Machine Learning, 4274-4283, 2019	58*	2019
Is private learning possible with instance encoding? N Carlini, S Deng, S Garg, S Jha, S Mahloujifar, M Mahmoody, A Thakurta, ... 2021 IEEE Symposium on Security and Privacy (SP), 410-427, 2021	55*	2021
Can Adversarially Robust Learning Leverage Computational Hardness? S Mahloujifar, M Mahmoody [edit] Saeed Mahloujifar, Mohammad Mahmoody ; Proceedings of the 30th …, 2019	39	2019
Property inference from poisoning S Mahloujifar, E Ghosh, M Chase 2022 IEEE Symposium on Security and Privacy (SP), 1120-1137, 2022	31*	2022
Learning under -Tampering Attacks S Mahloujifar, DI Diochnos, M Mahmoody Proceedings of Algorithmic Learning Theory, PMLR 83:572-596, 2018., 2018	28	2018
Blockwise p-Tampering Attacks on Cryptographic Primitives, Extractors, and Learners S Mahloujifar, M Mahmoody Theory of Cryptography: 15th International Conference, TCC 2017, Baltimore …, 2017	24	2017
Model-targeted poisoning attacks with provable convergence F Suya, S Mahloujifar, A Suri, D Evans, Y Tian International Conference on Machine Learning, 10000-10010, 2021	23*	2021
Empirically measuring concentration: Fundamental limits on intrinsic robustness S Mahloujifar, X Zhang, M Mahmoody, D Evans Advances in Neural Information Processing Systems 32, 2019	20	2019
Sparsefed: Mitigating model poisoning attacks in federated learning with sparsification A Panda, S Mahloujifar, AN Bhagoji, S Chakraborty, P Mittal International Conference on Artificial Intelligence and Statistics, 7587-7624, 2022	18	2022
Mitigating membership inference attacks by {Self-Distillation} through a novel ensemble architecture X Tang, S Mahloujifar, L Song, V Shejwalkar, M Nasr, A Houmansadr, ... 31st USENIX Security Symposium (USENIX Security 22), 1433-1450, 2022	18	2022
Adversarially robust learning could leverage computational hardness S Garg, S Jha, S Mahloujifar, M Mahmoody Proceedings of the 31st International Conference on Algorithmic Learning …, 2020	18	2020
Lower bounds for adversarially robust pac learning DI Diochnos, S Mahloujifar, M Mahmoody arXiv preprint arXiv:1906.05815, 2019	18	2019
{PatchCleanser}: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier C Xiang, S Mahloujifar, P Mittal 31st USENIX Security Symposium (USENIX Security 22), 2065-2082, 2022	14	2022
Parameterizing activation functions for adversarial robustness S Dai, S Mahloujifar, P Mittal 2022 IEEE Security and Privacy Workshops (SPW), 80-87, 2022	13	2022
Computational concentration of measure: Optimal bounds, reductions, and more O Etesami, S Mahloujifar, M Mahmoody Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020	13	2020
Near linear-time community detection in networks with hardly detectable community structure A Rezaei, SM Far, M Soleymani Proceedings of the 2015 IEEE/ACM International Conference on Advances in …, 2015	10*	2015
Membership inference on word embedding and beyond S Mahloujifar, HA Inan, M Chase, E Ghosh, M Hasegawa arXiv preprint arXiv:2106.11384, 2021	7	2021

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