Duality between Feature Selection and Data Clustering Conference Paper

abstract

• 2016 IEEE. The feature-selection problem is formulated from an information-theoretic perspective. We show that the problem can be efficiently solved by a recently proposed info-clustering paradigm. This reveals a fundamental duality between feature selection and data clustering, which is a consequence of a more general duality between the principal partition and the principal lattice of partitions in combinatorial optimization.

name of conference

• 2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

authors

• Liu, Tie

published proceedings

• 2016 54TH ANNUAL ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING (ALLERTON)

author list (cited authors)

• Chan, C., Al-Bashabsheh, A., Zhou, Q., & Liu, T.

citation count

• 4

complete list of authors

• Chan, Chung||Al-Bashabsheh, Ali||Zhou, Qiaoqiao||Liu, Tie

publication date

• January 2016

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• n2474-0195ISSN  Journal

Digital Object Identifier (DOI)

• 10.1109/allerton.2016.7852222

International Standard Book Number (ISBN) 13

• 9781509045495

start page

• 142

end page

• 147