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http://users.cecs.anu.edu.au/~williams/papers/P132.pdf
1448 BernhardScholkop¨ fetal. Notethatifºapproaches0,theupperboundariesontheLagrangemul- tiplierstendtoin”nity,thatis,thesecondinequalityconstraintinequa-tion3 ...
https://dl.acm.org/citation.cfm?id=1119749
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 ...Cited by: 4577
https://www.researchgate.net/publication/220499623_Estimating_Support_of_a_High-Dimensional_Distribution
Estimating the Support of a High-Dimensional Distribution 1447 Since nonzero slack variables ξ i are penalized in the objective function, we can expect that if w and ρ solve this problem, then ...
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. We propose a […]Cited by: 4577
http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.39.912
BibTeX @MISC{Schölkopf99estimatingthe, author = {Bernhard Schölkopf and John C. Platt and John Shawe-taylor and Alex J. Smola and Robert C. Williamson}, title = {Estimating the Support of a High-Dimensional Distribution}, year = {1999}}
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
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
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://openresearch-repository.anu.edu.au/handle/1885/69943
Jan 22, 2019 · Home » ANU Research » ANU Scholarly Output » ANU Research Publications » Estimating the Support of a High-dimensional Distribution Estimating the Support of a High-dimensional Distribution. link to publisher version. Statistics; Export Reference to BibTeX; ... Suppose you are given some data set drawn from an underlying probability ...Cited by: 4577
https://core.ac.uk/display/45852707
Estimating the support of a high-dimensional distribution. ... BibTex; Full citation; Abstract. 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 ...Cited by: 4577
http://users.cecs.anu.edu.au/~williams/papers/P132.pdf
1448 BernhardScholkop¨ fetal. Notethatifºapproaches0,theupperboundariesontheLagrangemul- tiplierstendtoin”nity,thatis,thesecondinequalityconstraintinequa-tion3 ...
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.researchgate.net/publication/220499623_Estimating_Support_of_a_High-Dimensional_Distribution
Estimating the Support of a High-Dimensional Distribution 1447 Since nonzero slack variables ξ i are penalized in the objective function, we can expect that if w and ρ solve this problem, then ...
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. We propose a […]Cited by: 4577
http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.39.912
BibTeX @MISC{Schölkopf99estimatingthe, author = {Bernhard Schölkopf and John C. Platt and John Shawe-taylor and Alex J. Smola and Robert C. Williamson}, title = {Estimating the Support of a High-Dimensional Distribution}, year = {1999}}
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
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
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://core.ac.uk/display/45852707
Estimating the support of a high-dimensional distribution. ... BibTex; Full citation; Abstract. 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 ...Cited by: 4577
http://www.math.univ-toulouse.fr/~agarivie/Telecom/apprentissage/articles/OneClasslong.pdf
Estimating the Support of a High-Dimensional Distribution Bernhard Sch¨olkopf , John C. Platt , John Shawe-Taylor , Alex J. Smola , Robert C. Williamson Microsoft Research Ltd, 1 Guildhall Street, Cambridge CB2 3NH, UK Microsoft Research, 1 Microsoft Way, Redmond, WA, USA Royal Holloway, University of London, Egham, UK
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