Proximal optimization for fuzzy subspace clustering

Authors

Arthur Guillon, Sorbonne Université
Marie Jeanne Lesot, Sorbonne Université
Christophe Marsala, Sorbonne Université
Nikhil R. Pal, Indian Statistical Institute, Kolkata

Document Type

Conference Article

Publication Title

Communications in Computer and Information Science

Abstract

This paper proposes a fuzzy partitioning subspace clustering algorithm that minimizes a variant of the FCM cost function with a weighted Euclidean distance and a penalty term. To this aim it considers the framework of proximal optimization. It establishes the expression of the proximal operator for the considered cost function and derives PFSCM, an algorithm combining proximal descent and alternate optimization. Experiments show the relevance of the proposed approach.

First Page

675

Last Page

686

DOI

10.1007/978-3-319-40596-4_56

Publication Date

1-1-2016

Recommended Citation

Guillon, Arthur; Lesot, Marie Jeanne; Marsala, Christophe; and Pal, Nikhil R., "Proximal optimization for fuzzy subspace clustering" (2016). Conference Articles. 782.
https://digitalcommons.isical.ac.in/conf-articles/782