‪Ambuj Tewari | अम्बुज तिवारी‬

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Inderjit S. DhillonDistinguished Scientist at Google & Professor of Computer Science at UT Austin, Ex-VP at Amazon在 cs.utexas.edu 的電子郵件地址已通過驗證
Peter BartlettProfessor, EECS and Statistics, UC Berkeley在 cs.berkeley.edu 的電子郵件地址已通過驗證
Karthik SridharanCornell University, University of Pennsylvania, Toyota Technological Institute在 ttic.edu 的電子郵件地址已通過驗證
George MichailidisProfessor of Statistics and Computer Science在 ufl.edu 的電子郵件地址已通過驗證
Mohamad Kazem Shirani FaradonbehSouthern Methodist University在 smu.edu 的電子郵件地址已通過驗證
Susan MurphyHarvard University在 g.harvard.edu 的電子郵件地址已通過驗證
Nagarajan NatarajanResearcher, Microsoft Research India在 microsoft.com 的電子郵件地址已通過驗證
Alexander RakhlinProfessor, MIT在 mit.edu 的電子郵件地址已通過驗證
Sham M KakadeHarvard University在 seas.harvard.edu 的電子郵件地址已通過驗證
Pradeep RavikumarProfessor, School of Computer Science, Carnegie Mellon University在 cs.cmu.edu 的電子郵件地址已通過驗證
Shai Shalev-ShwartzThe Hebrew University在 cs.huji.ac.il 的電子郵件地址已通過驗證
Paul ZimmermanUniversity of Michigan在 umich.edu 的電子郵件地址已通過驗證
Jacob AbernethyAssistant Professor, University of Michigan在 umich.edu 的電子郵件地址已通過驗證
Ziping XuPostdoc Fellow at Harvard University在 fas.harvard.edu 的電子郵件地址已通過驗證
Yangyi LuPhD student of Statistics, University of Michigan在 umich.edu 的電子郵件地址已通過驗證
Jack GoetzMeta在 umich.edu 的電子郵件地址已通過驗證
Vinod RamanUniversity of Michigan在 umich.edu 的電子郵件地址已通過驗證
Predrag KlasnjaAssociate Professor, School of Information, University of Michigan在 umich.edu 的電子郵件地址已通過驗證
Prateek JainGoogle Research India在 google.com 的電子郵件地址已通過驗證
Aditya ModiMicrosoft在 umich.edu 的電子郵件地址已通過驗證

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Ambuj Tewari | अम्बुज तिवारी

Professor, Statistics and EECS, University of Michigan

在 umich.edu 的電子郵件地址已通過驗證 - 首頁

Machine Learning Statistics Data Science Sequential Decision Making Optimization


標題按引用次數排序按年份排序按標題排序	引用次數引用次數	年份
Just in time adaptive interventions (JITAIs): An organizing framework for ongoing health behavior support I Nahum-Shani, SN Smith, B Spring, LM Collins, K Witkiewitz, A Tewari, ... Annals of Behavioral Medicine 52 (6), 446-462, 2018	1949*	2018
Learning with noisy labels N Natarajan, IS Dhillon, PK Ravikumar, A Tewari Advances in neural information processing systems 26, 2013	1446	2013
Microrandomized trials: An experimental design for developing just-in-time adaptive interventions. P Klasnja, EB Hekler, S Shiffman, A Boruvka, D Almirall, A Tewari, ... Health Psychology 34 (S), 1220, 2015	659	2015
Stochastic methods for l₁ regularized loss minimization S Shalev-Shwartz, A Tewari Proceedings of the 26th Annual International Conference on Machine Learning …, 2009	527	2009
PAC subset selection in stochastic multi-armed bandits S Kalyanakrishnan, A Tewari, P Auer, P Stone Proceedings of the 29th International Conference on Machine Learning (ICML …, 2012	450	2012
On the complexity of linear prediction: Risk bounds, margin bounds, and regularization SM Kakade, K Sridharan, A Tewari Advances in neural information processing systems 21, 2008	442	2008
Composite objective mirror descent. JC Duchi, S Shalev-Shwartz, Y Singer, A Tewari Colt 10, 14-26, 2010	425	2010
On the Consistency of Multiclass Classification Methods. A Tewari, PL Bartlett Journal of Machine Learning Research 8 (5), 2007	370	2007
Smoothness, low noise and fast rates N Srebro, K Sridharan, A Tewari Advances in neural information processing systems 23, 2010	324	2010
REGAL: A regularization based algorithm for reinforcement learning in weakly communicating MDPs PL Bartlett, A Tewari arXiv preprint arXiv:1205.2661, 2012	313	2012
On iterative hard thresholding methods for high-dimensional M-estimation P Jain, A Tewari, P Kar Advances in Neural Information Processing Systems, 685-693, 2014	269	2014
From ads to interventions: Contextual bandits in mobile health A Tewari, SA Murphy Mobile health: sensors, analytic methods, and applications, 495-517, 2017	249	2017
Mixture proportion estimation via kernel embeddings of distributions H Ramaswamy, C Scott, A Tewari International conference on machine learning, 2052-2060, 2016	235	2016
Online bandit learning against an adaptive adversary: from regret to policy regret R Arora, O Dekel, A Tewari arXiv preprint arXiv:1206.6400, 2012	228	2012
Regularization techniques for learning with matrices SM Kakade, S Shalev-Shwartz, A Tewari The Journal of Machine Learning Research 13 (1), 1865-1890, 2012	221	2012
Exploiting longer cycles for link prediction in signed networks KY Chiang, N Natarajan, A Tewari, IS Dhillon Proceedings of the 20th ACM international conference on Information and …, 2011	217	2011
Optimal strategies and minimax lower bounds for online convex games J Abernethy, PL Bartlett, A Rakhlin, A Tewari Proceedings of the 21st annual conference on learning theory, 414-424, 2008	206	2008
On the generalization ability of online strongly convex programming algorithms SM Kakade, A Tewari Advances in neural information processing systems 21, 2008	204	2008
Efficient bandit algorithms for online multiclass prediction SM Kakade, S Shalev-Shwartz, A Tewari Proceedings of the 25th international conference on Machine learning, 440-447, 2008	203	2008
Prediction and clustering in signed networks: a local to global perspective KY Chiang, CJ Hsieh, N Natarajan, IS Dhillon, A Tewari The Journal of Machine Learning Research 15 (1), 1177-1213, 2014	184	2014

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