Satyen Kale
Satyen Kale
Staff Research Scientist, Google Research
google.com의 이메일 확인됨 - 홈페이지
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On the convergence of adam and beyond
SJ Reddi, S Kale, S Kumar
arXiv preprint arXiv:1904.09237, 2019
11502019
Logarithmic regret algorithms for online convex optimization
E Hazan, A Agarwal, S Kale
Machine Learning 69 (2), 169-192, 2007
9732007
The multiplicative weights update method: A meta-algorithm and applications
S Arora, E Hazan, S Kale
Theory of Computing 8 (1), 121-164, 2012
7842012
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
4722007
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
3192014
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
2342007
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
2302011
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
2022014
Projection-free Online Learning
E Hazan, S Kale
Arxiv preprint arXiv:1206.4657, 2012
1802012
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
1802011
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
1802006
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
1562011
Commentary on “Online Optimization with Gradual Variations”
S Kale
154*
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
1422005
Extracting certainty from uncertainty: Regret bounded by variation in costs
E Hazan, S Kale
Machine learning 80 (2-3), 165-188, 2010
1372010
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
1252020
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
1252020
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
1202010
O (/spl radic/log n) approximation to SPARSEST CUT in O/spl tilde/(n/sup 2/) time
S Arora, E Hazan, S Kale
45th Annual IEEE Symposium on Foundations of Computer Science, 238-247, 2004
119*2004
Efficient aggregation algorithms for probabilistic data
TS Jayram, S Kale, E Vee
Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete …, 2007
1182007
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