Jerry Li

Citirano

	Sve	Od 2019.
Citati	9637	9091
H-indeks	36	35
i10-indeks	62	61

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Dan AlistarhProfessor at IST AustriaPotvrđena adresa e-pošte na ist.ac.at
Sitan ChenAssistant Professor of Computer Science, Harvard UniversityPotvrđena adresa e-pošte na seas.harvard.edu
Ilias DiakonikolasUniversity of Wisconsin-MadisonPotvrđena adresa e-pošte na wisc.edu
Milan VojnovicProfessor, Department of Statistics, LSEPotvrđena adresa e-pošte na lse.ac.uk
Ryota TomiokaMicrosoft Research AI for SciencePotvrđena adresa e-pošte na microsoft.com
Gautam KamathAssistant Professor @ University of Waterloo, Faculty Member @ Vector InstitutePotvrđena adresa e-pošte na uwaterloo.ca
Daniel KaneUniversity of California, San DiegoPotvrđena adresa e-pošte na ucsd.edu
Ankur MoitraNorbert Wiener Professor of Mathematics, MITPotvrđena adresa e-pošte na mit.edu
Ludwig SchmidtStanford University and AnthropicPotvrđena adresa e-pošte na cs.washington.edu
Alistair StewartWeb3 foundationPotvrđena adresa e-pošte na web3.foundation
Kevin TianAssistant Professor, University of Texas at AustinPotvrđena adresa e-pošte na cs.utexas.edu
Samuel B. HopkinsMassachusetts Institute of TechnologyPotvrđena adresa e-pošte na mit.edu
Jordan CotlerHarvard UniversityPotvrđena adresa e-pošte na fas.harvard.edu
Hsin-Yuan Huang (Robert)California Institute of Technology, Google Quantum AIPotvrđena adresa e-pošte na caltech.edu
Aleksander MądryMITPotvrđena adresa e-pošte na mit.edu
Allen LiuMassachusetts Institute of TechnologyPotvrđena adresa e-pošte na mit.edu
Ilya RazenshteynCipherMode LabsPotvrđena adresa e-pošte na mit.edu
Demjan GrubicGooglePotvrđena adresa e-pošte na google.com
Hadi SalmanOpenAI, MITPotvrđena adresa e-pošte na mit.edu
Greg YangxAIPotvrđena adresa e-pošte na x.ai

Prati

Jerry Li

University of Washington

Potvrđena adresa e-pošte na cs.washington.edu - Početna stranica

Learning Theory Machine Learning Distributed Computing Quantum Information Theory


Naslov Poredaj po navodima Poredaj po godini Poredaj po naslovu	Citirano Citirano	Godina
QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding D Alistarh, D Grubic, J Li, R Tomioka, M Vojnovic Advances in Neural Information Processing Systems, 1707-1718, 2017	2027	2017
Spectral signatures in backdoor attacks B Tran, J Li, A Madry Advances in neural information processing systems 31, 2018	892	2018
Provably robust deep learning via adversarially trained smoothed classifiers H Salman, J Li, I Razenshteyn, P Zhang, H Zhang, S Bubeck, G Yang Advances in neural information processing systems 32, 2019	605	2019
Robust estimators in high-dimensions without the computational intractability I Diakonikolas, G Kamath, D Kane, J Li, A Moitra, A Stewart SIAM Journal on Computing 48 (2), 742-864, 2019	547	2019
Quantum advantage in learning from experiments HY Huang, M Broughton, J Cotler, S Chen, J Li, M Mohseni, H Neven, ... Science 376 (6598), 1182-1186, 2022	516	2022
Aligning ai with shared human values D Hendrycks, C Burns, S Basart, A Critch, J Li, D Song, J Steinhardt arXiv preprint arXiv:2008.02275, 2020	441	2020
Byzantine stochastic gradient descent D Alistarh, Z Allen-Zhu, J Li Advances in neural information processing systems 31, 2018	348	2018
Sever: A robust meta-algorithm for stochastic optimization I Diakonikolas, G Kamath, D Kane, J Li, J Steinhardt, A Stewart International Conference on Machine Learning, 1596-1606, 2019	339	2019
Being robust (in high dimensions) can be practical I Diakonikolas, G Kamath, DM Kane, J Li, A Moitra, A Stewart International Conference on Machine Learning, 999-1008, 2017	276	2017
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions S Chen, S Chewi, J Li, Y Li, A Salim, AR Zhang arXiv preprint arXiv:2209.11215, 2022	260	2022
ZipML: Training linear models with end-to-end low precision, and a little bit of deep learning H Zhang, J Li, K Kara, D Alistarh, J Liu, C Zhang International Conference on Machine Learning, 4035-4043, 2017	253*	2017
Randomized smoothing of all shapes and sizes G Yang, T Duan, JE Hu, H Salman, I Razenshteyn, J Li International Conference on Machine Learning, 10693-10705, 2020	225	2020
Automatic prompt optimization with" gradient descent" and beam search R Pryzant, D Iter, J Li, YT Lee, C Zhu, M Zeng arXiv preprint arXiv:2305.03495, 2023	224	2023
Mixture models, robustness, and sum of squares proofs SB Hopkins, J Li Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing …, 2018	203	2018
Privately learning high-dimensional distributions G Kamath, J Li, V Singhal, J Ullman Conference on Learning Theory, 1853-1902, 2019	167	2019
The spraylist: A scalable relaxed priority queue D Alistarh, J Kopinsky, J Li, N Shavit Proceedings of the 20th ACM SIGPLAN Symposium on Principles and Practice of …, 2015	151	2015
Robustly learning a gaussian: Getting optimal error, efficiently I Diakonikolas, G Kamath, DM Kane, J Li, A Moitra, A Stewart Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete …, 2018	148	2018
Computationally efficient robust sparse estimation in high dimensions S Balakrishnan, SS Du, J Li, A Singh Conference on Learning Theory, 169-212, 2017	143	2017
Exponential separations between learning with and without quantum memory S Chen, J Cotler, HY Huang, J Li 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS …, 2022	131	2022
Quantum entropy scoring for fast robust mean estimation and improved outlier detection Y Dong, S Hopkins, J Li Advances in Neural Information Processing Systems 32, 2019	112	2019

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