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Ambuj Tewari | अम्बुज तिवारी
Ambuj Tewari | अम्बुज तिवारी
Professor, Statistics and EECS, University of Michigan
Verified email at umich.edu - Homepage
Title
Cited by
Cited by
Year
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
1609*2018
Learning with noisy labels
N Natarajan, IS Dhillon, PK Ravikumar, A Tewari
Advances in neural information processing systems 26, 2013
12862013
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
5732015
Stochastic methods for l1 regularized loss minimization
S Shalev-Shwartz, A Tewari
Proceedings of the 26th Annual International Conference on Machine Learning …, 2009
5122009
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
4062012
Composite objective mirror descent.
JC Duchi, S Shalev-Shwartz, Y Singer, A Tewari
COLT 10, 14-26, 2010
4012010
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
4012008
On the Consistency of Multiclass Classification Methods.
A Tewari, PL Bartlett
Journal of Machine Learning Research 8 (5), 2007
3432007
Smoothness, low noise and fast rates
N Srebro, K Sridharan, A Tewari
Advances in neural information processing systems 23, 2010
2912010
REGAL: A regularization based algorithm for reinforcement learning in weakly communicating MDPs
PL Bartlett, A Tewari
arXiv preprint arXiv:1205.2661, 2012
2842012
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
2402014
From ads to interventions: Contextual bandits in mobile health
A Tewari, SA Murphy
Mobile health: sensors, analytic methods, and applications, 495-517, 2017
2132017
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
2082011
Regularization techniques for learning with matrices
SM Kakade, S Shalev-Shwartz, A Tewari
The Journal of Machine Learning Research 13 (1), 1865-1890, 2012
2062012
Mixture proportion estimation via kernel embeddings of distributions
H Ramaswamy, C Scott, A Tewari
International conference on machine learning, 2052-2060, 2016
2002016
Online bandit learning against an adaptive adversary: from regret to policy regret
R Arora, O Dekel, A Tewari
arXiv preprint arXiv:1206.6400, 2012
1972012
On the generalization ability of online strongly convex programming algorithms
SM Kakade, A Tewari
Advances in neural information processing systems 21, 2008
1942008
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
1912008
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
1882008
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
1752014
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