PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Ranking on Data Manifolds
Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet and Bernhard Schölkopf
In: NIPS 2003, Vancouver, Canada(2004).

Abstract

The Google search engine has enjoyed a huge success with its web page ranking algorithm, which exploits global, rather than local, hyperlink structure of the web using random walks. Here we propose a simple universal ranking algorithm for data lying in the Euclidean space, such as text or image data. The core idea of our method is to rank the data with respect to the intrinsic manifold structure collectively revealed by a great amount of data. Encouraging experimental results from synthetic, image, and text data illustrate the validity of our method.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:478
Deposited By:Dengyong Zhou
Deposited On:23 December 2004