| Theoretical models of learning to learn J Baxter Learning to learn, 71-94, 1998 | 1127* | 1998 |
| Infinite-horizon policy-gradient estimation J Baxter, PL Bartlett J. Artif. Intell. Res. (JAIR) 15, 319-350, 2001 | 1000* | 2001 |
| Boosting algorithms as gradient descent L Mason, J Baxter, PL Bartlett, MR Frean Advances in neural information processing systems 12 (NIPS 1999), 512-518, 2000 | 970* | 2000 |
| A model of inductive bias learning J Baxter J. Artif. Intell. Res. (JAIR) 12, 149-198, 2000 | 909 | 2000 |
| Variance reduction techniques for gradient estimates in reinforcement learning E Greensmith, PL Bartlett, J Baxter Journal of Machine Learning Research 5 (Nov), 1471-1530, 2004 | 382 | 2004 |
| A Bayesian/information theoretic model of learning to learn via multiple task sampling J Baxter Machine learning 28 (1), 7-39, 1997 | 374 | 1997 |
| Functional gradient techniques for combining hypotheses L Mason, J Baxter, PL Bartlett, M Frean Advances in Large-Margin Classifiers, 221-246, 2000 | 352 | 2000 |
| Learning to play chess using temporal differences J Baxter, A Tridgell, L Weaver Machine Learning 40 (3), 243-263, 2000 | 328* | 2000 |
| Learning Internal Representations (COLT 1995) J Baxter COLT '95: Proceedings of the eighth annual conference on Computational …, 1995 | 260* | 1995 |
| Improved generalization through explicit optimization of margins L Mason, PL Bartlett, J Baxter Machine Learning 38 (3), 243-255, 2000 | 169 | 2000 |
| Reinforcement learning in POMDP's via direct gradient ascent J Baxter, PL Bartlett ICML '00 Proceedings of the Seventeenth International Conference on Machine …, 2000 | 140 | 2000 |
| Direct gradient-based reinforcement learning J Baxter, PL Bartlett Circuits and Systems, 2000. Proceedings. ISCAS 2000 Geneva. The 2000 IEEE …, 2000 | 116 | 2000 |
| Scaling internal-state policy-gradient methods for POMDPs D Aberdeen, J Baxter ICML '02 Proceedings of the Nineteenth International Conference on Machine …, 2002 | 107 | 2002 |
| A multi-agent, policy-gradient approach to network routing N Tao, J Baxter, L Weaver ICML '01 Proceedings of the Eighteenth International Conference on Machine …, 2001 | 83 | 2001 |
| The Evolution of Learning Algorithms for Artificial Neural Networks J Baxter Complex systems: From biology to computation, 313, 1993 | 72 | 1993 |
| Experiments in parameter learning using temporal differences J Baxter, A Tridgell, L Weaver ICGA Journal 21 (2), 84-99, 1998 | 68 | 1998 |
| Direct optimization of margins improves generalization in combined classifiers L Mason, PL Bartlett, J Baxter Advances in neural information processing systems 11 (NIPS 1998), 288-294, 1999 | 62 | 1999 |
| Estimation and approximation bounds for gradient-based reinforcement learning PL Bartlett, J Baxter Journal of Computer and System Sciences 64 (1), 133-150, 2002 | 58 | 2002 |
| Tdleaf (): Combining temporal difference learning with game-tree search J Baxter, A Tridgell, L Weaver Australian Journal of Intelligent Information Processing Systems 5 (1), 39-43, 1998 | 48 | 1998 |
| Emmerald: a fast matrix–matrix multiply using Intel's SSE instructions D Aberdeen, J Baxter Concurrency and Computation: Practice and Experience 13 (2), 103-119, 2001 | 43 | 2001 |
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyVerified email at cs.berkeley.edu
