October 30, 2019 to November 1, 2019
Ingrid Daubechies Auditorium
America/New_York timezone

The why and how of nonnegative matrix factorization

Nov 1, 2019, 11:35 AM
25m
2nd Floor (Ingrid Daubechies Auditorium)

2nd Floor

Ingrid Daubechies Auditorium

162 5th avenue, 2nd floor, New York NY, 10010

Speaker

Johannes Friedrich (CCB)

Description

Nonnegative matrix factorization (NMF) has become a widely used tool for the analysis of high-dimensional data as it automatically extracts sparse and meaningful features from a set of nonnegative data vectors. I first illustrate this property of NMF on some applications. Then I address the problem of solving NMF, which is NP-hard in general, and review some standard NMF algorithms. Finally, I briefly describe an online NMF algorithm, which scales up gracefully to large data sets.

Presentation materials