‪Ambuj Tewari | अम्बुज तिवारी‬

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Inderjit S. DhillonDistinguished Scientist at Google & Professor of Computer Science at UT Austin, Ex-VP at AmazonDirección de correo verificada de cs.utexas.edu
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyDirección de correo verificada de cs.berkeley.edu
Karthik SridharanCornell University, University of Pennsylvania, Toyota Technological InstituteDirección de correo verificada de ttic.edu
George MichailidisProfessor of Statistics and Computer ScienceDirección de correo verificada de ufl.edu
Mohamad Kazem Shirani FaradonbehSouthern Methodist UniversityDirección de correo verificada de smu.edu
Susan MurphyHarvard UniversityDirección de correo verificada de g.harvard.edu
Nagarajan NatarajanResearcher, Microsoft Research IndiaDirección de correo verificada de microsoft.com
Alexander RakhlinProfessor, MITDirección de correo verificada de mit.edu
Sham M KakadeHarvard UniversityDirección de correo verificada de seas.harvard.edu
Pradeep RavikumarProfessor, School of Computer Science, Carnegie Mellon UniversityDirección de correo verificada de cs.cmu.edu
Shai Shalev-ShwartzThe Hebrew UniversityDirección de correo verificada de cs.huji.ac.il
Paul ZimmermanUniversity of MichiganDirección de correo verificada de umich.edu
Jacob AbernethyAssistant Professor, University of MichiganDirección de correo verificada de umich.edu
Ziping XuPostdoc Fellow at Harvard UniversityDirección de correo verificada de fas.harvard.edu
Yangyi LuPhD student of Statistics, University of MichiganDirección de correo verificada de umich.edu
Jack GoetzMetaDirección de correo verificada de umich.edu
Predrag KlasnjaAssociate Professor, School of Information, University of MichiganDirección de correo verificada de umich.edu
Vinod RamanUniversity of MichiganDirección de correo verificada de umich.edu
Prateek JainGoogle Research IndiaDirección de correo verificada de google.com
Aditya ModiMicrosoftDirección de correo verificada de umich.edu

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Ambuj Tewari | अम्बुज तिवारी

Professor, Statistics and EECS, University of Michigan

Dirección de correo verificada de umich.edu - Página principal

Machine Learning Statistics Data Science Sequential Decision Making Optimization


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
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	1445	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	658	2015
Stochastic methods for l₁ regularized loss minimization S Shalev-Shwartz, A Tewari Proceedings of the 26th Annual International Conference on Machine Learning …, 2009	526	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	449	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	424	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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