Stability Analysis for Local Transductive Regression Algorithms

Abstract:

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In this paper, the stability of local transductive regression algorithms is studied by adopting a strategy which adjusts the sample set by removing one or two elements from it. A sufficient condition for uniform stability is given. The result of our work shows that if a local transductive regression algorithm uses square loss, and if for any x, a kernel function K(x, x) has a limited upper bound, then the local transductive regression algorithm which minimizes the standard form will have good uniform stability.

Info:

Periodical:

Edited by:

Yanwen Wu

Pages:

438-443

DOI:

10.4028/www.scientific.net/AMR.267.438

Citation:

W. Gao et al., "Stability Analysis for Local Transductive Regression Algorithms", Advanced Materials Research, Vol. 267, pp. 438-443, 2011

Online since:

June 2011

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Price:

$35.00

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