Ambuj Tewari | अम्बुज तिवारी

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Karthik SridharanCornell University, University of Pennsylvania, Toyota Technological InstituteAdresse e-mail validée de ttic.edu
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyAdresse e-mail validée de cs.berkeley.edu
Inderjit S. DhillonDistinguished Scientist at Google & Professor of Computer Science at UT Austin, Ex-VP at AmazonAdresse e-mail validée de cs.utexas.edu
George MichailidisProfessor of Statistics and Computer ScienceAdresse e-mail validée de ufl.edu
Mohamad Kazem Shirani FaradonbehDepartment of Statistics, University of GeorgiaAdresse e-mail validée de uga.edu
Susan MurphyHarvard UniversityAdresse e-mail validée de g.harvard.edu
Nagarajan NatarajanResearcher, Microsoft Research IndiaAdresse e-mail validée de microsoft.com
Alexander RakhlinProfessor, MITAdresse e-mail validée de mit.edu
Sham M KakadeHarvard UniversityAdresse e-mail validée de seas.harvard.edu
Pradeep RavikumarProfessor, School of Computer Science, Carnegie Mellon UniversityAdresse e-mail validée de cs.cmu.edu
Shai Shalev-ShwartzThe Hebrew UniversityAdresse e-mail validée de cs.huji.ac.il
Jacob AbernethyAssistant Professor, University of MichiganAdresse e-mail validée de umich.edu
Prateek JainGoogle Research IndiaAdresse e-mail validée de google.com
Predrag KlasnjaAssociate Professor, School of Information, University of MichiganAdresse e-mail validée de umich.edu
Paul ZimmermanUniversity of MichiganAdresse e-mail validée de umich.edu
Ziping XuPhD student, University of MichiganAdresse e-mail validée de umich.edu
Young Hun JungMicrosoftAdresse e-mail validée de microsoft.com
Jack GoetzMetaAdresse e-mail validée de umich.edu
Yangyi LuPhD student of Statistics, University of MichiganAdresse e-mail validée de umich.edu
Nathan SrebroProfessor, TTIC and University of ChicagoAdresse e-mail validée de ttic.edu

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Ambuj Tewari | अम्बुज तिवारी

Professor, Statistics and EECS, University of Michigan

Adresse e-mail validée de umich.edu - Page d'accueil

Machine Learning Statistics Data Science Sequential Decision Making Optimization


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
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	1232*	2018
Learning with noisy labels N Natarajan, IS Dhillon, PK Ravikumar, A Tewari Advances in neural information processing systems 26, 2013	1069	2013
Stochastic methods for l₁ regularized loss minimization S Shalev-Shwartz, A Tewari Proceedings of the 26th Annual International Conference on Machine Learning …, 2009	488	2009
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	464	2015
Composite objective mirror descent. JC Duchi, S Shalev-Shwartz, Y Singer, A Tewari COLT 10, 14-26, 2010	372	2010
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	363	2008
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	347	2012
On the Consistency of Multiclass Classification Methods. A Tewari, PL Bartlett Journal of Machine Learning Research 8 (5), 2007	310	2007
REGAL: A regularization based algorithm for reinforcement learning in weakly communicating MDPs PL Bartlett, A Tewari arXiv preprint arXiv:1205.2661, 2012	260	2012
Smoothness, low noise and fast rates N Srebro, K Sridharan, A Tewari Advances in neural information processing systems 23, 2010	247	2010
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	215	2014
Regularization techniques for learning with matrices SM Kakade, S Shalev-Shwartz, A Tewari The Journal of Machine Learning Research 13 (1), 1865-1890, 2012	196	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	189	2011
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	181	2008
Online bandit learning against an adaptive adversary: from regret to policy regret R Arora, O Dekel, A Tewari arXiv preprint arXiv:1206.6400, 2012	178	2012
On the generalization ability of online strongly convex programming algorithms SM Kakade, A Tewari Advances in Neural Information Processing Systems 21, 2008	178	2008
Optimal strategies and minimax lower bounds for online convex games J Abernethy, PL Bartlett, A Rakhlin, A Tewari	170	2008
From ads to interventions: Contextual bandits in mobile health A Tewari, SA Murphy Mobile Health: Sensors, Analytic Methods, and Applications, 495-517, 2017	167	2017
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	166	2014
Mixture proportion estimation via kernel embeddings of distributions H Ramaswamy, C Scott, A Tewari International conference on machine learning, 2052-2060, 2016	161	2016

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