Ambuj Tewari | अम्बुज तिवारी
Ambuj Tewari | अम्बुज तिवारी
Professor, Department of Statistics and Department of EECS, University of Michigan
Verified email at - Homepage
Cited by
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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
Learning with noisy labels
N Natarajan, IS Dhillon, PK Ravikumar, A Tewari
Advances in neural information processing systems 26, 1196-1204, 2013
Stochastic Methods for l1-regularized Loss Minimization
S Shalev-Shwartz, A Tewari
The Journal of Machine Learning Research 12, 1865-1892, 2011
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
Composite Objective Mirror Descent.
JC Duchi, S Shalev-Shwartz, Y Singer, A Tewari
COLT, 14-26, 2010
On the complexity of linear prediction: Risk bounds, margin bounds, and regularization
SM Kakade, K Sridharan, A Tewari
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
On the Consistency of Multiclass Classification Methods.
A Tewari, PL Bartlett
Journal of Machine Learning Research 8 (5), 2007
REGAL: A regularization based algorithm for reinforcement learning in weakly communicating MDPs
PL Bartlett, A Tewari
arXiv preprint arXiv:1205.2661, 2012
Smoothness, low noise and fast rates
N Srebro, K Sridharan, A Tewari
Advances in neural information processing systems 23, 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
Regularization techniques for learning with matrices
SM Kakade, S Shalev-Shwartz, A Tewari
The Journal of Machine Learning Research 13 (1), 1865-1890, 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
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
Optimal strategies and minimax lower bounds for online convex games
J Abernethy, PL Bartlett, A Rakhlin, A Tewari
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
Online bandit learning against an adaptive adversary: from regret to policy regret
R Arora, O Dekel, A Tewari
arXiv preprint arXiv:1206.6400, 2012
Prediction and validation of gene-disease associations using methods inspired by social network analyses
UM Singh-Blom, N Natarajan, A Tewari, JO Woods, IS Dhillon, ...
PloS one 8 (5), e58977, 2013
On the generalization ability of online strongly convex programming algorithms
SM Kakade, A Tewari
Advances in Neural Information Processing Systems, 801-808, 2009
On the nonasymptotic convergence of cyclic coordinate descent methods
A Saha, A Tewari
SIAM Journal on Optimization 23 (1), 576-601, 2013
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