Accession Number:

ADA588861

Title:

New Theory and Algorithms for Scalable Data Fusion

Descriptive Note:

Final rept. 30 Sep 2009-30 Apr 2013

Corporate Author:

CALIFORNIA UNIV BERKELEY DEPT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCE

Personal Author(s):

Report Date:

2013-07-14

Pagination or Media Count:

13.0

Abstract:

The research performed under this grant served to address the modeling, algorithmic and theoretical challenges associated with problems of large-scale data fusion. Significant research accomplishments included a the development of message passing algorithms for distributed optimization and inference b the formulation and analysis of convex relaxations for estimating low-rank matrices from data c the development of non-parametric methods for solving high-dimensional prediction problems and d the analysis and implementation of methods for graphical model selection.

Subject Categories:

  • Information Science
  • Numerical Mathematics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE