Nonnegative Matrix Factorization for Clustering Haesun Park
[email protected] School of Computational Science and Engineering Georgia Institute of Technology Atlanta, GA, USA MMDS July 2012
This work was supported in part by the National Science Foundation.
Haesun Park
[email protected]
Nonnegative Matrix Factorization for Clustering
Co-authors
Jingu Kim
Nokia
Da Kuang
CSE, Georgia Tech
Yunlong He
Math, Georgia Tech
Haesun Park
[email protected]
Nonnegative Matrix Factorization for Clustering
Outline Overview of NMF Fast algorithms for NMF with Frobenius norm Block Coordinate Descent (BCD) framework On convergence Some other algorithms
Variations of NMF Nonnegative Tensor factorization NMF with Bregman divergences, ...
NMF for Clustering Sparse NMF via regularization Symmetric NMF for graph clustering
Experimental Results Summary
Haesun Park
[email protected]
Nonnegative Matrix Factorization for Clustering
Nonnegative Matrix Factorization (NMF) (Lee&Seung 99, Paatero&Tapper 94)
Given A ∈ R+ m×n and a desired rank k