Matthew E. Taylor's Publications

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Transfer Learning via Inter-Task Mappings for Temporal Difference Learning

Matthew E. Taylor, Peter Stone, and Yaxin Liu. Transfer Learning via Inter-Task Mappings for Temporal Difference Learning. Journal of Machine Learning Research, 8(1):2125–2167, 2007.

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Abstract

A growing number of security applications are being developed and deployed to explicitly reduce risk from adversaries' actions. However, there are many challenges when attempting to evaluate such systems, both in the lab and in the real world. Traditional evaluations used by computer scientists, such as runtime analysis and optimality proofs, may be largely irrelevant. The primary contribution of this paper is to provide a preliminary framework which can guide the evaluation of such systems and to apply the framework to the evaluation of ARMOR (a system deployed at LAX since August 2007). This framework helps to determine what evaluations could, and should, be run in order to measure a system's overall utility. A secondary contribution of this paper is to help familiarize our community with some of the difficulties inherent in evaluating deployed applications, focusing on those in security domains.

BibTeX Entry

@Article{JMLR07-taylor,
	Author="Matthew E.\ Taylor and Peter Stone and Yaxin Liu",
	title="Transfer Learning via Inter-Task Mappings for Temporal Difference Learning",
        journal="Journal of Machine Learning Research",
	year="2007",
	volume="8",number="1",
        pages="2125--2167",
abstract="A growing number of security applications are being
    developed and deployed to explicitly reduce risk from adversaries'
    actions. However, there are many challenges when attempting to
    \emph{evaluate} such systems, both in the lab and in the real
    world. Traditional evaluations used by computer scientists, such
    as runtime analysis and optimality proofs, may be largely
    irrelevant. The primary contribution of this paper is to provide a
    preliminary framework which can guide the evaluation of such
    systems and to apply the framework to the evaluation of ARMOR (a
    system deployed at LAX since August 2007). This framework helps to
    determine what evaluations could, and should, be run in order to
    measure a system's overall utility. A secondary contribution of
    this paper is to help familiarize our community with some of the
    difficulties inherent in evaluating deployed applications,
    focusing on those in security domains."
}

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