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All publications by Alekh Agarwal
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Learning to Search Better than Your Teacher
Kai-wei Chang, Akshay Krishnamurthy, Alekh Agarwal, Hal Daume and John Langford
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


A Lower Bound for the Optimization of Finite Sums
Alekh Agarwal and Leon Bottou
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Efficient and Parsimonious Agnostic Active Learning
Tzu-kuo Huang, Alekh Agarwal, Daniel J. Hsu, John Langford and Robert E. Schapire
Advances in Neural Information Processing Systems 28, 2015


Fast Convergence of Regularized Learning in Games
Vasilis Syrgkanis, Alekh Agarwal, Haipeng Luo and Robert E. Schapire
Advances in Neural Information Processing Systems 28, 2015


Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits
Alekh Agarwal, Daniel Hsu, Satyen Kale, John Langford, Lihong Li and Robert Schapire
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Least Squares Revisited: Scalable Approaches for Multi-class Prediction
Alekh Agarwal, Sham Kakade, Nikos Karampatziakis, Le Song and Gregory Valiant
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Scalable Non-linear Learning with Adaptive Polynomial Expansions
Alekh Agarwal, Alina Beygelzimer, Daniel J. Hsu, John Langford and Matus J. Telgarsky
Advances in Neural Information Processing Systems 27, 2014


Selective sampling algorithms for cost-sensitive multiclass prediction
Alekh Agarwal
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions
Alekh Agarwal, Sahand Negahban and Martin J. Wainwright
Advances in Neural Information Processing Systems 25, 2012


Contextual Bandit Learning with Predictable Rewards
Alekh Agarwal, Miroslav Dudík, Satyen Kale, John Langford and Robert E. Schapire
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Stochastic convex optimization with bandit feedback
Alekh Agarwal, Dean P. Foster, Daniel J. Hsu, Sham M. Kakade and Alexander Rakhlin
Advances in Neural Information Processing Systems 24, 2011


Distributed Delayed Stochastic Optimization
Alekh Agarwal and John C. Duchi
Advances in Neural Information Processing Systems 24, 2011


Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions
Alekh Agarwal, Sahand Negahban and Martin J. Wainwright
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Fast global convergence rates of gradient methods for high-dimensional statistical recovery
Alekh Agarwal, Sahand Negahban and Martin J. Wainwright
Advances in Neural Information Processing Systems 23, 2010


Distributed Dual Averaging In Networks
Alekh Agarwal, Martin J. Wainwright and John C. Duchi
Advances in Neural Information Processing Systems 23, 2010


Optimal Allocation Strategies for the Dark Pool Problem
Alekh Agarwal, Peter L. Bartlett and Max Dama
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Information-theoretic lower bounds on the oracle complexity of convex optimization
Alekh Agarwal, Martin J. Wainwright, Peter L. Bartlett and Pradeep K. Ravikumar
Advances in Neural Information Processing Systems 22, 2009


Message-passing for graph-structured linear programs: proximal projections, convergence and rounding schemes
Pradeep D. Ravikumar, Alekh Agarwal and Martin J. Wainwright
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Learning random walks to rank nodes in graphs
Alekh Agarwal and Soumen Chakrabarti
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


An Analysis of Inference with the Universum
Olivier Chapelle, Alekh Agarwal, Fabian H. Sinz and Bernhard Schölkopf
Advances in Neural Information Processing Systems 20, 2007