Accession Number:

ADA621842

Title:

Unsupervised Learning from Multiple Information Sources Based on Non-negative Matrix Factorization (NMF)

Descriptive Note:

Final rept. 19 Aug 2010-18 Aug 2014

Corporate Author:

FLORIDA INTERNATIONAL UNIV MIAMI

Personal Author(s):

Report Date:

2015-01-20

Pagination or Media Count:

15.0

Abstract:

In many real-world applications, the data are naturally multi-modal, in the sense that they are represented by multiple sets of features. In general, with the availability of multiple information sources, it is a challenging problem to conduct integrated exploratory analysis with the aim of extracting more information than what is possible from only a single source.

Subject Categories:

  • Information Science
  • Statistics and Probability
  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE