Classifier-based affinities for clustering sets of vectors

Dario García-Garcia; Raul Santos-Rodriguez; Emilio Parrado-Hernández

doi:10.1109/MLSP.2012.6349760

Classifier-based affinities for clustering sets of vectors

Dario García-Garcia^*
, Raul Santos-Rodriguez
, Emilio Parrado-Hernández

^*Corresponding author for this work

Intelligent Systems Laboratory

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

1 Citation (Scopus)

Abstract

We focus on the task of clustering sets of vectors. This can be seen as a special case of sequence clustering when the dynamics are not taken into account. We propose to use the error probability of binary classifiers to obtain a measure of the affinity between two sets so that a standard similarity-based clustering algorithm can be applied.

Original language	English
Title of host publication	2012 IEEE International Workshop on Machine Learning for Signal Processing - Proceedings of MLSP 2012
DOIs	https://doi.org/10.1109/MLSP.2012.6349760
Publication status	Published - 2012
Event	2012 22nd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2012 - Santander, Spain Duration: 23 Sept 2012 → 26 Sept 2012

Publication series

Name	IEEE International Workshop on Machine Learning for Signal Processing, MLSP
ISSN (Print)	2161-0363
ISSN (Electronic)	2161-0371

Conference

Conference	2012 22nd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2012
Country/Territory	Spain
City	Santander
Period	23/09/12 → 26/09/12

Bibliographical note

Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.

Keywords

Sequence clustering
sets of vectors
speaker clustering

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10.1109/MLSP.2012.6349760

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García-Garcia, D., Santos-Rodriguez, R., & Parrado-Hernández, E. (2012). Classifier-based affinities for clustering sets of vectors. In 2012 IEEE International Workshop on Machine Learning for Signal Processing - Proceedings of MLSP 2012 Article 6349760 (IEEE International Workshop on Machine Learning for Signal Processing, MLSP). https://doi.org/10.1109/MLSP.2012.6349760

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title = "Classifier-based affinities for clustering sets of vectors",

abstract = "We focus on the task of clustering sets of vectors. This can be seen as a special case of sequence clustering when the dynamics are not taken into account. We propose to use the error probability of binary classifiers to obtain a measure of the affinity between two sets so that a standard similarity-based clustering algorithm can be applied.",

keywords = "Sequence clustering, sets of vectors, speaker clustering",

author = "Dario Garc{\'i}a-Garcia and Raul Santos-Rodriguez and Emilio Parrado-Hern{\'a}ndez",

note = "Copyright: Copyright 2012 Elsevier B.V., All rights reserved.; 2012 22nd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2012 ; Conference date: 23-09-2012 Through 26-09-2012",

year = "2012",

doi = "10.1109/MLSP.2012.6349760",

language = "English",

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García-Garcia, D, Santos-Rodriguez, R & Parrado-Hernández, E 2012, Classifier-based affinities for clustering sets of vectors. in 2012 IEEE International Workshop on Machine Learning for Signal Processing - Proceedings of MLSP 2012., 6349760, IEEE International Workshop on Machine Learning for Signal Processing, MLSP, 2012 22nd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2012, Santander, Spain, 23/09/12. https://doi.org/10.1109/MLSP.2012.6349760

Classifier-based affinities for clustering sets of vectors. / García-Garcia, Dario; Santos-Rodriguez, Raul; Parrado-Hernández, Emilio.
2012 IEEE International Workshop on Machine Learning for Signal Processing - Proceedings of MLSP 2012. 2012. 6349760 (IEEE International Workshop on Machine Learning for Signal Processing, MLSP).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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AU - Santos-Rodriguez, Raul

AU - Parrado-Hernández, Emilio

PY - 2012

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N2 - We focus on the task of clustering sets of vectors. This can be seen as a special case of sequence clustering when the dynamics are not taken into account. We propose to use the error probability of binary classifiers to obtain a measure of the affinity between two sets so that a standard similarity-based clustering algorithm can be applied.

AB - We focus on the task of clustering sets of vectors. This can be seen as a special case of sequence clustering when the dynamics are not taken into account. We propose to use the error probability of binary classifiers to obtain a measure of the affinity between two sets so that a standard similarity-based clustering algorithm can be applied.

KW - Sequence clustering

KW - sets of vectors

KW - speaker clustering

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DO - 10.1109/MLSP.2012.6349760

M3 - Conference Contribution (Conference Proceeding)

AN - SCOPUS:84870719435

SN - 9781467310260

T3 - IEEE International Workshop on Machine Learning for Signal Processing, MLSP

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T2 - 2012 22nd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2012

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ER -

Classifier-based affinities for clustering sets of vectors

Abstract

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Bibliographical note

Keywords

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