Jonathan Baxter
Jonathan Baxter
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Theoretical models of learning to learn
J Baxter
Learning to learn, 71-94, 1998
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
Infinite-horizon policy-gradient estimation
J Baxter, PL Bartlett
J. Artif. Intell. Res. (JAIR) 15, 319-350, 2001
A model of inductive bias learning
J Baxter
J. Artif. Intell. Res. (JAIR) 12, 149-198, 2000
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning.
E Greensmith, PL Bartlett, J Baxter
Journal of Machine Learning Research 5 (9), 2004
A Bayesian/information theoretic model of learning to learn via multiple task sampling
J Baxter
Machine learning 28 (1), 7-39, 1997
Functional gradient techniques for combining hypotheses
L Mason, J Baxter, PL Bartlett, M Frean
Advances in Large-Margin Classifiers, 221-246, 2000
Learning to play chess using temporal differences
J Baxter, A Tridgell, L Weaver
Machine Learning 40 (3), 243-263, 2000
Learning Internal Representations (COLT 1995)
J Baxter
COLT '95: Proceedings of the eighth annual conference on Computational …, 1995
Improved generalization through explicit optimization of margins
L Mason, PL Bartlett, J Baxter
Machine Learning 38 (3), 243-255, 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
Direct gradient-based reinforcement learning
J Baxter, PL Bartlett
Circuits and Systems, 2000. Proceedings. ISCAS 2000 Geneva. The 2000 IEEE …, 2000
Scaling internal-state policy-gradient methods for POMDPs
D Aberdeen, J Baxter
ICML '02 Proceedings of the Nineteenth International Conference on Machine …, 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
The Evolution of Learning Algorithms for Artificial Neural Networks
J Baxter
Complex systems: From biology to computation, 313, 1993
Experiments in parameter learning using temporal differences
J Baxter, A Tridgell, L Weaver
ICGA Journal 21 (2), 84-99, 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
Estimation and approximation bounds for gradient-based reinforcement learning
PL Bartlett, J Baxter
Journal of Computer and System Sciences 64 (1), 133-150, 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
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
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Artikelen 1–20