Estimation and clustering with infinite rankings

Marina Meilă; Le Bao

Estimation and clustering with infinite rankings

Marina Meilă, Le Bao

Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence, PMLR R6:393-402, 2008.

Abstract

This paper presents a natural extension of stagewise ranking to the the case of infinitely many items. We introduce the infinite generalized Mallows model (IGM), describe its properties and give procedures to estimate it from data. For estimation of multimodal distributions we introduce the Exponential-Blurring-Mean-Shift nonparametric clustering algorithm. The experiments highlight the properties of the new model and demonstrate that infinite models can be simple, elegant and practical.

Cite this Paper

BibTeX

@InProceedings{pmlr-vR6-meila08a,
  title = 	 {Estimation and clustering with infinite rankings},
  author =       {Meil\u{a}, Marina and Bao, Le},
  booktitle = 	 {Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence},
  pages = 	 {393--402},
  year = 	 {2008},
  editor = 	 {McAllester, David A. and Myllymäki, Petri},
  volume = 	 {R6},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {09--12 Jul},
  publisher =    {PMLR},
  pdf = 	 {https://raw.githubusercontent.com/mlresearch/r6/main/assets/meila08a/meila08a.pdf},
  url = 	 {https://proceedings.mlr.press/r6/meila08a.html},
  abstract = 	 {This paper presents a natural extension of stagewise ranking to the the case of infinitely many items. We introduce the infinite generalized Mallows model (IGM), describe its properties and give procedures to estimate it from data. For estimation of multimodal distributions we introduce the Exponential-Blurring-Mean-Shift nonparametric clustering algorithm. The experiments highlight the properties of the new model and demonstrate that infinite models can be simple, elegant and practical.},
  note =         {Reissued by PMLR on 09 October 2024.}
}

Endnote

%0 Conference Paper
%T Estimation and clustering with infinite rankings
%A Marina Meilă
%A Le Bao
%B Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence
%C Proceedings of Machine Learning Research
%D 2008
%E David A. McAllester
%E Petri Myllymäki	
%F pmlr-vR6-meila08a
%I PMLR
%P 393--402
%U https://proceedings.mlr.press/r6/meila08a.html
%V R6
%X This paper presents a natural extension of stagewise ranking to the the case of infinitely many items. We introduce the infinite generalized Mallows model (IGM), describe its properties and give procedures to estimate it from data. For estimation of multimodal distributions we introduce the Exponential-Blurring-Mean-Shift nonparametric clustering algorithm. The experiments highlight the properties of the new model and demonstrate that infinite models can be simple, elegant and practical.
%Z Reissued by PMLR on 09 October 2024.

APA

Meilă, M. & Bao, L.. (2008). Estimation and clustering with infinite rankings. Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence, in Proceedings of Machine Learning Research R6:393-402 Available from https://proceedings.mlr.press/r6/meila08a.html. Reissued by PMLR on 09 October 2024.

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