Satyen Kale

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Citations	12383	8871
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Elad HazanProfessor at Princeton University and Director Google AI PrincetonVerified email at princeton.edu
Sashank J. ReddiResearch Scientist, Google ResearchVerified email at cs.cmu.edu
Sanjiv KumarGoogle Fellow, VP, Google ResearchVerified email at google.com
Mehryar MohriHead, Learning Theory Team, Google Research; Professor, Courant Institute of Mathematical Sciences.Verified email at google.com
Sanjeev AroraProfessor of Computer Science, Princeton UniversityVerified email at cs.princeton.edu
Ananda Theertha SureshSenior Research Scientist, Google New YorkVerified email at google.com
Sai Praneeth KarimireddyPostdoc, UC BerkeleyVerified email at berkeley.edu
Sebastian Urban StichCISPA Helmholtz Center for Information SecurityVerified email at cispa.de
Robert SchapireMicrosoft ResearchVerified email at microsoft.com
John LangfordMicrosoft Research New YorkVerified email at hunch.net
Karthik SridharanCornell University, University of Pennsylvania, Toyota Technological InstituteVerified email at ttic.edu
Boaz BarakHarvard UniversityVerified email at boazbarak.org
Tong ZhangHKUSTVerified email at tongzhang-ml.org
Daniel HsuColumbia UniversityVerified email at cs.columbia.edu
C. SeshadhriUniversity of California, Santa CruzVerified email at ucsc.edu
Haipeng LuoAssociate Professor, University of Southern CaliforniaVerified email at usc.edu
Kunal TalwarApple IncVerified email at apple.com
Kamalika ChaudhuriProfessor of Computer Science, UCSD. Research Scientist, Meta AIVerified email at ucsd.edu
Cynthia DworkMicrosoft ResearchVerified email at microsoft.com
Frank McSherryMaterialize, Inc.Verified email at materialize.io

Satyen Kale

Staff Research Scientist, Google Research

Verified email at google.com - Homepage

Machine Learning Optimization Algorithms


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
On the convergence of adam and beyond SJ Reddi, S Kale, S Kumar 6th International Conference on Learning Representations, 2018	2326	2018
SCAFFOLD: Stochastic controlled averaging for federated learning SP Karimireddy, S Kale, M Mohri, S Reddi, S Stich, AT Suresh International Conference on Machine Learning, 5132-5143, 2020	1281	2020
Logarithmic regret algorithms for online convex optimization E Hazan, A Agarwal, S Kale Machine Learning 69 (2), 169-192, 2007	1190	2007
The multiplicative weights update method: A meta-algorithm and applications S Arora, E Hazan, S Kale Theory of Computing 8 (1), 121-164, 2012	1045	2012
Privacy, accuracy, and consistency too: a holistic solution to contingency table release B Barak, K Chaudhuri, C Dwork, S Kale, F McSherry, K Talwar Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART Symposium on …, 2007	561	2007
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits A Agarwal, D Hsu, S Kale, J Langford, L Li, RE Schapire arXiv preprint arXiv:1402.0555, 2014	478	2014
Adaptive methods for nonconvex optimization M Zaheer, S Reddi, D Sachan, S Kale, S Kumar Advances in neural information processing systems 31, 2018	316	2018
Efficient Optimal Learning for Contextual Bandits M Dudik, D Hsu, S Kale, N Karampatziakis, J Langford, L Reyzin, T Zhang Arxiv preprint arXiv:1106.2369, 2011	315	2011
Beyond the regret minimization barrier: optimal algorithms for stochastic strongly-convex optimization. E Hazan, S Kale Journal of Machine Learning Research 15 (1), 2489-2512, 2014	274	2014
A combinatorial, primal-dual approach to semidefinite programs S Arora, S Kale Proceedings of the thirty-ninth annual ACM symposium on Theory of computing …, 2007	251	2007
Algorithms for portfolio management based on the newton method A Agarwal, E Hazan, S Kale, RE Schapire Proceedings of the 23rd international conference on Machine learning, 9-16, 2006	246	2006
Projection-free Online Learning E Hazan, S Kale Arxiv preprint arXiv:1206.4657, 2012	237	2012
Online optimization with gradual variations CK Chiang, T Yang, CJ Lee, M Mahdavi, CJ Lu, R Jin, S Zhu Conference on Learning Theory, 6.1-6.20, 2012	214	2012
Who Moderates the Moderators? Crowdsourcing Abuse Detection in User-Generated Content A Ghosh, S Kale, P McAfee Proceedings of the 12th ACM conference on Electronic commerce, 167-176, 2011	205	2011
A Field Guide to Federated Optimization J Wang, Z Charles, Z Xu, G Joshi, HB McMahan, M Al-Shedivat, G Andrew, ... arXiv preprint arXiv:2107.06917, 2021	180	2021
Extracting certainty from uncertainty: Regret bounded by variation in costs E Hazan, S Kale Machine learning 80 (2-3), 165-188, 2010	164	2010
Fast algorithms for approximate semidefinite programming using the multiplicative weights update method S Arora, E Hazan, S Kale 46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05), 339-348, 2005	161	2005
Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization E Hazan, S Kale Proceedings of the 24th Annual Conference on Learning Theory, 421-436, 2011	156	2011
Estimating Training Data Influence by Tracing Gradient Descent G Pruthi, F Liu, S Kale, M Sundararajan Advances in Neural Information Processing Systems 33, 2020	135	2020
O(\logn) Approximation to SPARSEST CUT in ̃O(n^2) Time S Arora, E Hazan, S Kale SIAM Journal on Computing 39 (5), 1748-1771, 2010	130	2010

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