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All publications by Ambuj Tewari
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Generalization error bounds for learning to rank: Does the length of document lists matter?
Ambuj Tewari and Sougata Chaudhuri
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Convex Calibrated Surrogates for Hierarchical Classification
Harish Ramaswamy, Ambuj Tewari and Shivani Agarwal
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Fighting Bandits with a New Kind of Smoothness
Jacob D. Abernethy, Chansoo Lee and Ambuj Tewari
Advances in Neural Information Processing Systems 28, 2015


Predtron: A Family of Online Algorithms for General Prediction Problems
Prateek Jain, Nagarajan Natarajan and Ambuj Tewari
Advances in Neural Information Processing Systems 28, 2015


Alternating Minimization for Regression Problems with Vector-valued Outputs
Prateek Jain and Ambuj Tewari
Advances in Neural Information Processing Systems 28, 2015


On Iterative Hard Thresholding Methods for High-dimensional M-Estimation
Prateek Jain, Ambuj Tewari and Purushottam Kar
Advances in Neural Information Processing Systems 27, 2014


Learning with Noisy Labels
Nagarajan Natarajan, Inderjit Dhillon, Pradeep Ravikumar and Ambuj Tewari
Advances in Neural Information Processing Systems 26, 2013


Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses
Harish G. Ramaswamy, Shivani Agarwal and Ambuj Tewari
Advances in Neural Information Processing Systems 26, 2013


Feature Clustering for Accelerating Parallel Coordinate Descent
Chad Scherrer, Ambuj Tewari, Mahantesh Halappanavar and David Haglin
Advances in Neural Information Processing Systems 25, 2012


Scaling Up Coordinate Descent Algorithms for Large $\ell_1$ Regularization Problems
Chad Scherrer, Mahantesh Halappanavar, Ambuj Tewari and David Haglin
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


PAC Subset Selection in Stochastic Multi-armed Bandits
Shivaram Kalyanakrishnan, Ambuj Tewari, Peter Auer and Peter Stone
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret
Raman Arora, Ofer Dekel and Ambuj Tewari
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Perturbation based Large Margin Approach for Ranking
Eunho Yang, Ambuj Tewari and Pradeep D. Ravikumar
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


On the Universality of Online Mirror Descent
Nati Srebro, Karthik Sridharan and Ambuj Tewari
Advances in Neural Information Processing Systems 24, 2011


Nearest Neighbor based Greedy Coordinate Descent
Inderjit S. Dhillon, Pradeep K. Ravikumar and Ambuj Tewari
Advances in Neural Information Processing Systems 24, 2011


Online Learning: Stochastic, Constrained, and Smoothed Adversaries
Alexander Rakhlin, Karthik Sridharan and Ambuj Tewari
Advances in Neural Information Processing Systems 24, 2011


Orthogonal Matching Pursuit with Replacement
Prateek Jain, Ambuj Tewari and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 24, 2011


Greedy Algorithms for Structurally Constrained High Dimensional Problems
Ambuj Tewari, Pradeep K. Ravikumar and Inderjit S. Dhillon
Advances in Neural Information Processing Systems 24, 2011


Improved Regret Guarantees for Online Smooth Convex Optimization with Bandit Feedback
Ankan Saha and Ambuj Tewari
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


On NDCG Consistency of Listwise Ranking Methods
Pradeep D. Ravikumar, Ambuj Tewari and Eunho Yang
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Smoothness, Low Noise and Fast Rates
Nathan Srebro, Karthik Sridharan and Ambuj Tewari
Advances in Neural Information Processing Systems 23, 2010


Online Learning: Random Averages, Combinatorial Parameters, and Learnability
Alexander Rakhlin, Karthik Sridharan and Ambuj Tewari
Advances in Neural Information Processing Systems 23, 2010


Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity
Sham Kakade, Ohad Shamir, Karthik Sindharan and Ambuj Tewari
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Stochastic methods for {\it l}$_{\mbox{1}}$ regularized loss minimization
Shai Shalev-shwartz and Ambuj Tewari
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Efficient bandit algorithms for online multiclass prediction
Sham M. Kakade, Shai Shalev-shwartz and Ambuj Tewari
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization
Sham M. Kakade, Karthik Sridharan and Ambuj Tewari
Advances in Neural Information Processing Systems 21, 2008


On the Generalization Ability of Online Strongly Convex Programming Algorithms
Sham M. Kakade and Ambuj Tewari
Advances in Neural Information Processing Systems 21, 2008


On the Consistency of Multiclass Classification Methods
Ambuj Tewari and Peter L. Bartlett
Journal of Machine Learning Research, 2007


Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs
Ambuj Tewari and Peter L. Bartlett
Advances in Neural Information Processing Systems 20, 2007


Sparseness vs Estimating Conditional Probabilities: Some Asymptotic Results
Peter L. Bartlett and Ambuj Tewari
Journal of Machine Learning Research, 2007


Sample Complexity of Policy Search with Known Dynamics
Peter L. Bartlett and Ambuj Tewari
Advances in Neural Information Processing Systems 19, 2006