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All publications by Gavin Taylor
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An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation Accuracy
Gavin Taylor, Connor Geer and David Piekut
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes
Marek Petrik, Gavin Taylor, Ronald Parr and Shlomo Zilberstein
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Kernelized value function approximation for reinforcement learning
Gavin Taylor and Ronald Parr
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning
Ronald Parr, Lihong Li, Gavin Taylor, Christopher Painter-wakefield and Michael L. Littman
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008