NIPS Proceedings^β

Ambuj Tewari

18 Papers

Alternating Minimization for Regression Problems with Vector-valued Outputs (2015)

Fighting Bandits with a New Kind of Smoothness (2015)

Predtron: A Family of Online Algorithms for General Prediction Problems (2015)

On Iterative Hard Thresholding Methods for High-dimensional M-Estimation (2014)

Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses (2013)

Learning with Noisy Labels (2013)

Feature Clustering for Accelerating Parallel Coordinate Descent (2012)

Greedy Algorithms for Structurally Constrained High Dimensional Problems (2011)

Nearest Neighbor based Greedy Coordinate Descent (2011)

Online Learning: Stochastic, Constrained, and Smoothed Adversaries (2011)

On the Universality of Online Mirror Descent (2011)

Orthogonal Matching Pursuit with Replacement (2011)

Online Learning: Random Averages, Combinatorial Parameters, and Learnability (2010)

Smoothness, Low Noise and Fast Rates (2010)

On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization (2008)

On the Generalization Ability of Online Strongly Convex Programming Algorithms (2008)

Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs (2007)

Sample Complexity of Policy Search with Known Dynamics (2006)