| * | 2009 |
|---|
| 13 | EE | Shai Shalev-Shwartz,
Ambuj Tewari:
Stochastic methods for l1 regularized loss minimization.
ICML 2009: 117 |
| 12 | EE | Sham M. Kakade,
Shai Shalev-Shwartz,
Ambuj Tewari:
Applications of strong convexity--strong smoothness duality to learning with matrices
CoRR abs/0910.0610: (2009) |
| 2008 |
|---|
| 11 | EE | Peter L. Bartlett,
Varsha Dani,
Thomas P. Hayes,
Sham Kakade,
Alexander Rakhlin,
Ambuj Tewari:
High-Probability Regret Bounds for Bandit Online Linear Optimization.
COLT 2008: 335-342 |
| 10 | EE | Jacob Abernethy,
Peter L. Bartlett,
Alexander Rakhlin,
Ambuj Tewari:
Optimal Stragies and Minimax Lower Bounds for Online Convex Games.
COLT 2008: 415-424 |
| 9 | EE | Sham M. Kakade,
Shai Shalev-Shwartz,
Ambuj Tewari:
Efficient bandit algorithms for online multiclass prediction.
ICML 2008: 440-447 |
| 8 | EE | Sham M. Kakade,
Karthik Sridharan,
Ambuj Tewari:
On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization.
NIPS 2008: 793-800 |
| 7 | EE | Sham M. Kakade,
Ambuj Tewari:
On the Generalization Ability of Online Strongly Convex Programming Algorithms.
NIPS 2008: 801-808 |
| 2007 |
|---|
| 6 | EE | Ambuj Tewari,
Peter L. Bartlett:
Bounded Parameter Markov Decision Processes with Average Reward Criterion.
COLT 2007: 263-277 |
| 5 | EE | Ambuj Tewari,
Peter L. Bartlett:
Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs.
NIPS 2007 |
| 2006 |
|---|
| 4 | EE | Peter L. Bartlett,
Ambuj Tewari:
Sample Complexity of Policy Search with Known Dynamics.
NIPS 2006: 97-104 |
| 2005 |
|---|
| 3 | EE | Ambuj Tewari,
Peter L. Bartlett:
On the Consistency of Multiclass Classification Methods.
COLT 2005: 143-157 |
| 2004 |
|---|
| 2 | EE | Peter L. Bartlett,
Ambuj Tewari:
Sparseness Versus Estimating Conditional Probabilities: Some Asymptotic Results.
COLT 2004: 564-578 |
| 2002 |
|---|
| 1 | EE | Ambuj Tewari,
Utkarsh Srivastava,
P. Gupta:
A Parallel DFA Minimization Algorithm.
HiPC 2002: 34-40 |
