Accession Number:

ADA631568

Title:

Network Data: Statistical Theory and New Models

Descriptive Note:

Final rept. 15 Mar 2011-14 Mar 2015

Corporate Author:

CALIFORNIA UNIV BERKELEY SPONSORED PROJECTS OFFICE

Personal Author(s):

Report Date:

2016-02-17

Pagination or Media Count:

19.0

Abstract:

During this period of review, Bin Yu worked on many thrusts of high-dimensional statistical theory and methodologies. Her research covered a wide range of topics in statistics including analysis and methods for spectral clustering for sparse and structured networks 2,7,8,21, sparse modeling e.g. Lasso 4,10,11,17,18,19, statistical guarantees for the EM algorithm 3, statistical analysis of algorithm leveraging for solving big data problems 5, causal network modeling 15,20, stability as a general conceptframework for reproducible statistical discovery 9,13, and high-dimensional inference 12. Yu also collaborated with other research groups and Labs to conduct interdisciplinary research in areas including systems biology, neuroscience, remote sensing, document summarization, and social networks. For example, she has been collaborating with Dr. Frise et al. on constructing gene-gene interaction networks 1, with the Gallant Lab on understanding visual pathway of primates by using sparse coding 14, and with environmental scientists at JPL and Emory University to retrieval from NASA MISR remote sensing images aerosol index AOD for air pollution monitoring and management 6,16.

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE