Disentangling Gaussians.
The article discusses the Gaussian mixture model (GMM), a statistical moodel comprised of heterogeneous Gaussian sources, and presents an algorithm which is able to recover the parameters of Gaussians which has polynomial sample complexity and computational complexity. The article discusses one-dime...
| Publicado en: | Communications of the ACM Vol. 55; no. 2; pp. 113 - 121 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Association for Computing Machinery
Feb2012
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=71681543&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 71681543 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00010782 ACM jtl: Communications of the ACM issn: 00010782 maglogo: N pubinfo: dt: Feb2012 vid: 55 iid: 2 pid: 68 pub: Association for Computing Machinery artinfo: ui: 71681543 10.1145/2076450.2076474 ppf: 113 ppct: 8 formats: tig: atl: Disentangling Gaussians. aug: au: Kalai, Adam Tauman Moitra, Ankur Valiant, Gregory su: Gaussian distribution Distribution (Probability theory) Multidimensional databases Polynomials Computational complexity Algorithms sug: subj: Gaussian distribution Distribution (Probability theory) Multidimensional databases Polynomials Computational complexity Algorithms ab: The article discusses the Gaussian mixture model (GMM), a statistical moodel comprised of heterogeneous Gaussian sources, and presents an algorithm which is able to recover the parameters of Gaussians which has polynomial sample complexity and computational complexity. The article discusses one-dimensional GMM and discusses issues related to clustering, overlapping Gaussians, and decomposition. The authors argue that their algorithm can provide a basis for developing estimators or other algorithms with practical utilities. pubtype: Periodical doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2012 holdings: @attributes: islocal: N |
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