| 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 |
Inderjit S. DhillonDistinguished Scientist at Google & Professor of Computer Science at UT Austin, Ex-VP at Amazoncs.utexas.edu의 이메일 확인됨
