An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation Accuracy
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Gavin Taylor, Connor Geer, David Piekut
An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation Accuracy
ICML, 2014.

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@inproceedings{ICML-c2-2014-TaylorGP,
	author        = "Gavin Taylor and Connor Geer and David Piekut",
	booktitle     = "{Proceedings of the 31st International Conference on Machine Learning, Cycle 2}",
	ee            = "http://jmlr.org/proceedings/papers/v32/taylor14.html",
	pages         = "451--459",
	publisher     = "{JMLR.org}",
	series        = "{JMLR Proceedings}",
	title         = "{An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation Accuracy}",
	volume        = 32,
	year          = 2014,
}

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