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Tewari, Ambuj - Toyota Technological Institute at Chicago
Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs
Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity
Sample complexity of policy search with known Peter L. Bartlett
Sparseness Versus Estimating Conditional Probabilities: Some Asymptotic Results
On the Consistency of Multiclass Classification Methods
Journal of Machine Learning Research 8 (2007) 1007-1025 Submitted 10/05; Revised 12/06; Published 5/07 On the Consistency of Multiclass Classification Methods
Convex Games in Banach Spaces Karthik Sridharan
On the Finite Time Convergence of Cyclic Coordinate Descent Department of Computer Science
On the Generalization Ability of Online Strongly Convex Programming Algorithms
On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization
Bounded Parameter Markov Decision Processes with Average Reward Criterion
Journal of Machine Learning Research 8 (2007) 775-790 Submitted 6/06; Published 4/07 Sparseness vs Estimating Conditional Probabilities
A Parallel DFA Minimization Algorithm Ambuj Tewari, Utkarsh Srivastava, and P. Gupta
Composite Objective Mirror Descent John C. Duchi
Regularization Techniques for Learning with Matrices Sham M. Kakade
