The minimax distortion redundancy in empirical quantizer design

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  • dc.contributor.author Bartlett, Peter
  • dc.contributor.author Linder, Tamas
  • dc.contributor.author Lugosi, Gábor
  • dc.contributor.other Universitat Pompeu Fabra. Departament d'Economia i Empresa
  • dc.date.accessioned 2020-05-25T09:27:07Z
  • dc.date.available 2020-05-25T09:27:07Z
  • dc.date.issued 1997-01-01
  • dc.date.modified 2020-05-25T09:17:01Z
  • dc.description.abstract We obtain minimax lower and upper bounds for the expected distortion redundancy of empirically designed vector quantizers. We show that the mean squared distortion of a vector quantizer designed from $n$ i.i.d. data points using any design algorithm is at least $\Omega (n^{-1/2})$ away from the optimal distortion for some distribution on a bounded subset of ${\cal R}^d$. Together with existing upper bounds this result shows that the minimax distortion redundancy for empirical quantizer design, as a function of the size of the training data, is asymptotically on the order of $n^{1/2}$. We also derive a new upper bound for the performance of the empirically optimal quantizer.
  • dc.format.mimetype application/pdf*
  • dc.identifier https://econ-papers.upf.edu/ca/paper.php?id=198
  • dc.identifier.citation IEEE Transactions on Information Theory, 44, (1998), pp. 1802-1813
  • dc.identifier.uri http://hdl.handle.net/10230/743
  • dc.language.iso eng
  • dc.relation.ispartofseries Economics and Business Working Papers Series; 198
  • dc.rights L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
  • dc.subject.keyword estimation
  • dc.subject.keyword hypothesis testing
  • dc.subject.keyword statistical decision theory: operations research
  • dc.subject.keyword Statistics, Econometrics and Quantitative Methods
  • dc.title The minimax distortion redundancy in empirical quantizer design
  • dc.type info:eu-repo/semantics/workingPaper