Generating Multiple Hypotheses in Non-negative Matrix Factorization and Related Linear Models
Abstract
This proposal describes several novel directions for discovering multiple optima if they exist. As such,it is a fundamentally different tack than prior work in non-negative matrix factorization which outlines assumptions under which the discovered solutions are unique; instead of making assumptions—which may or may not be true—this proposal focuses on providing the domain expert a set of hypotheses to explore patterns in complex data.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 02, 2017
- Source ID
- FA95501710155
Entities
People
- Finale Doshi-velez
Organizations
- Air Force Office of Scientific Research
- President and Fellows of Harvard College
- United States Air Force