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Estimating the Support of a High-dimensional Distribution

Schoelkopf, Bernhard; Platt, John C; Shawe-Taylor, John; Smola, Alexander; Williamson, Robert

Description

Suppose you are given some data set drawn from an underlying probability distribution P and you want to estimate a "simple" subset S of input space such that the probability that a test point drawn from P lies outside of S equals some a priori specified value between 0 and 1. We propose a method to approach this problem by trying to estimate a function f that is positive on S and negative on the complement. The functional form of f is given by a kernel expansion in terms of a potentially small...[Show more]

CollectionsANU Research Publications
Date published: 2001
Type: Journal article
URI: http://hdl.handle.net/1885/69943
Source: Neural Computation
DOI: 10.1162/089976601750264965

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