Agglomerative multivariate information bottleneck

Noam Slonim; Nir Friedman; Naftali Tishby

Agglomerative multivariate information bottleneck

Noam Slonim, Nir Friedman, Naftali Tishby

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Scopus citations

Abstract

The information bottleneck method is an unsupervised model independent data organization technique. Given a joint distribution P(A,B), this method constructs a new variable T that extracts partitions, or clusters, over the values of ,4 that are informative about B. In a recent paper, we introduced a general principled framework for multivariate extensions of the information bottleneck method that allows us to consider multiple systems of data partitions that are inter-related. In this paper, we present a new family of simple agglomerative algorithms to construct such systems of inter-related clusters. We analyze the behavior of these algorithms and apply them to several real-life datasets.

Original language	English
Title of host publication	Advances in Neural Information Processing Systems 14 - Proceedings of the 2001 Conference, NIPS 2001
Publisher	Neural information processing systems foundation
ISBN (Print)	0262042088, 9780262042086
State	Published - 2002
Event	15th Annual Neural Information Processing Systems Conference, NIPS 2001 - Vancouver, BC, Canada Duration: 3 Dec 2001 → 8 Dec 2001

Publication series

Name	Advances in Neural Information Processing Systems
ISSN (Print)	1049-5258

Conference

Conference	15th Annual Neural Information Processing Systems Conference, NIPS 2001
Country/Territory	Canada
City	Vancouver, BC
Period	3/12/01 → 8/12/01

Cite this

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title = "Agglomerative multivariate information bottleneck",

abstract = "The information bottleneck method is an unsupervised model independent data organization technique. Given a joint distribution P(A,B), this method constructs a new variable T that extracts partitions, or clusters, over the values of ,4 that are informative about B. In a recent paper, we introduced a general principled framework for multivariate extensions of the information bottleneck method that allows us to consider multiple systems of data partitions that are inter-related. In this paper, we present a new family of simple agglomerative algorithms to construct such systems of inter-related clusters. We analyze the behavior of these algorithms and apply them to several real-life datasets.",

author = "Noam Slonim and Nir Friedman and Naftali Tishby",

year = "2002",

language = "אנגלית",

isbn = "0262042088",

series = "Advances in Neural Information Processing Systems",

publisher = "Neural information processing systems foundation",

booktitle = "Advances in Neural Information Processing Systems 14 - Proceedings of the 2001 Conference, NIPS 2001",

note = "15th Annual Neural Information Processing Systems Conference, NIPS 2001 ; Conference date: 03-12-2001 Through 08-12-2001",

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Slonim, N, Friedman, N & Tishby, N 2002, Agglomerative multivariate information bottleneck. in Advances in Neural Information Processing Systems 14 - Proceedings of the 2001 Conference, NIPS 2001. Advances in Neural Information Processing Systems, Neural information processing systems foundation, 15th Annual Neural Information Processing Systems Conference, NIPS 2001, Vancouver, BC, Canada, 3/12/01.

Agglomerative multivariate information bottleneck. / Slonim, Noam; Friedman, Nir; Tishby, Naftali.
Advances in Neural Information Processing Systems 14 - Proceedings of the 2001 Conference, NIPS 2001. Neural information processing systems foundation, 2002. (Advances in Neural Information Processing Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Tishby, Naftali

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Agglomerative multivariate information bottleneck

Abstract

Publication series

Conference

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