title: Non-negative matrix analysis in x-ray spectromicroscopy: choosing regularizers.
abstract: In x-ray spectromicroscopy, a set of images can be acquired across an absorption edge to reveal chemical speciation. We previously described the use of non-negative matrix approximation methods for improved classification and analysis of these types of data. We present here an approach to find appropriate values of regularization parameters for this optimization approach.
authors.affiliation: Dept. Physics & Astronomy, Northwestern University, Evanston, Illinois, USA.
authors.forename: Rachel
authors.initials: R
authors.lastname: Mak
authors.affiliation: Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois, USA.
authors.forename: Stefan M
authors.initials: SM
authors.lastname: Wild
authors.affiliation: X-ray Science Division, Advanced Photon Source, Argonne National Laboratory, Argonne, Illinois, USA; Dept. Physics & Astronomy, Northwestern University, Evanston, Illinois, USA.
authors.forename: Chris
authors.initials: C
authors.lastname: Jacobsen
keywords: multivariate statistical analysis; non-negative matrix analysis; optimization; x-ray microscopy; x-ray spectromicroscopy