Paper Title:
Stability Analysis for Local Transductive Regression Algorithms
  Abstract

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, Y. G. Zhang, L. Liang, "Stability Analysis for Local Transductive Regression Algorithms", Advanced Materials Research, Vol. 267, pp. 438-443, 2011
Online since
June 2011
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