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https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/tr-99-87.pdf
Estimating the Support of a High-Dimensional Distribution Bernhard Sch¨olkopf?, John C. Platt z, John Shawe-Taylor y, Alex J. Smola x, Robert C. Williamson x, Microsoft Research Ltd, 1 Guildhall Street, Cambridge CB2 3NH, UKCited by: 4577
https://www.microsoft.com/en-us/research/publication/estimating-the-support-of-a-high-dimensional-distribution/
Suppose you are given some dataset 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 is bounded by some a priori specified v between 0 and 1.Cited by: 4577
http://users.cecs.anu.edu.au/~williams/papers/P132.pdf
1444 BernhardScholkop¨ fetal. ”ed.Generally,theycanbecharacterizedasestimatingfunctionsofthedata, whichrevealsomethinginterestingabouttheunderlyingdistributions.For
http://alex.smola.org/papers/2001/SchPlaShaSmoetal01.pdf
Estimating the Support of a High-Dimensional Distribution 1445 of the probability mass. Estimators of the form C‘.fi/are called minimum volume estimators. Observe that for Cbeing all Borel measurable sets, C.1/is the support of the density p corresponding to P, assuming it exists.(Note that C.1/is well defined even when p does not exist.) For smaller classes C, C.1/is the
http://members.cbio.mines-paristech.fr/~jvert/svn/bibli/local/Scholkopf2001Estimating.pdf
Estimating the Support of a High-Dimensional Distribution 1445 of the probability mass. Estimators of the form C`(a)are called minimum volume estimators. Observe that forCbeing all Borel measurable sets,C(1)is the support of the densitypcorresponding toP, assuming it exists.(Note thatC(1)is well de” ned even whenpdoes not exist.)For smaller classesC,C(1)isthe
https://eprints.soton.ac.uk/259007/
Jul 01, 2001 · Estimating the Support of a High-Dimensional Distribution Estimating the Support of a High-Dimensional Distribution 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 ...Cited by: 4577
https://www.semanticscholar.org/paper/Estimating-the-Support-of-a-High-Dimensional-Sch%C3%B6lkopf-Platt/9cc912ae25797e5f7c0d73300d3968ad8339b411
Mathematics, Computer Science, Medicine; Published in Neural Computation 2001; DOI: 10.1162/089976601750264965 Estimating the Support of a High-Dimensional Distribution @article{Schlkopf2001EstimatingTS, title={Estimating the Support of a High-Dimensional Distribution}, author={Bernhard Sch{\"o}lkopf and John C. Platt and John Shawe-Taylor and …
https://www.mitpressjournals.org/doi/10.1162/089976601750264965
Mar 13, 2006 · Estimating the Support of a High-Dimensional Distribution Bernhard Schölkopf , John C. Platt , John Shawe-Taylor , Alex J. Smola and Robert C. Williamson Posted Online March 13, 2006Cited by: 4577
https://dl.acm.org/doi/10.1162/089976601750264965
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 ...
https://www.academia.edu/9321551/Estimating_the_Support_of_a_High-Dimensional_Distribution
Estimating the Support of a High-Dimensional Distribution
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