Results 81 to 90 of about 1,727,048 (195)
The British Journal of Sociology, Volume 77, Issue 4, Page 624-636, September 2026.ABSTRACT The 2000s have witnessed a significant, worldwide boom in new art museums founded by private, wealthy collectors. While the arts have long been a key arena for the remaking of elite distinction and the reproduction of inequalities, this surge in private museums has sparked much controversy.
Sara de Andrade Silva +2 more
wiley +1 more source
Using underapproximations for sparse nonnegative matrix factorization [PDF]
Nonnegative Matrix Factorization (NMF) has gathered a lot of attention in the last decade and has been successfully applied in numerous applications.
GILLIS, Nicolas, GLINEUR, François
core
Advanced Science, Volume 13, Issue 45, 13 August 2026.A single‐cell atlas of pancreatic ductal adenocarcinoma development reveals progressive ductal‐fibroblast‐immune crosstalk. Tumor‐derived LAMB3 drives the formation of immunosuppressive LRRC15+ fibroblasts through the ITGB1/FAK/MAPK/FOSL2 signaling. Glycolytic reprogramming upregulates LAMB3 and correlates with LRRC15+ fibroblast enrichment.
Xuqing Shi +23 more
wiley +1 more source
Nonnegative factorization and the maximum edge biclique problem [PDF]
Nonnegative matrix factorization (NMF) is a data analysis technique based on the approximation of a nonnegative matrix with a product of two nonnegative factors, which allows compression and interpretation of nonnegative data. In this paper, we study the
GILLIS, Nicolas, GLINEUR, François
core
VIEW, Volume 7, Issue 4, August 2026.In this work, we develop submicron‐resolution mapping of intracellular lipid elements (SMILE) as an extraction‐free vibrational spectroscopic imaging platform based on hyperspectral stimulated Raman scattering microscopy with a spectral analysis pipeline for pixel‐resolved lipid profiling.
Yihui Zhou +10 more
wiley +1 more source
On rationality of nonnegative matrix factorization [PDF]
, 2016 Nonnegative matrix factorization (NMF) is the problem of decomposing a given nonnegative n × m matrix M into a product of a nonnegative n × d matrix W and a nonnegative d × m matrix H.
Kiefer, Stefan +14 more
core +2 more sources
Journal of Microscopy, Volume 303, Issue 2, Page 194-215, August 2026.Abstract Grain identification in polycrystalline nanoparticles, for example, determining which crystal phases are present at each spatial location, is fundamental to materials characterisation. This is particularly challenging when grains overlap extensively, as commonly occurs in four‐dimensional scanning transmission electron microscopy (4D‐STEM ...
Wei Liu +5 more
wiley +1 more source
Heuristics for exact nonnegative matrix factorization [PDF]
, 2015 The exact nonnegative matrix factorization (exact NMF) problem is the following: given an m-by-n nonnegative matrix X and a factorization rank r, find, if possible, an m-by-r nonnegative matrix W and an r-by-n nonnegative matrix H such that X=WH. In this
Vandaele, Arnaud +3 more
core +1 more source
International Journal of Applied Mathematics and Computer Science, 2014 Nonnegative Matrix Factorization (NMF) is an important tool in data spectral analysis. However, when a mixing matrix or sources are not sufficiently sparse, NMF of an observation matrix is not unique.
Zdunek Rafał
doaj +1 more source
Similarity Learning-Induced Symmetric Nonnegative Matrix Factorization for Image Clustering
IEEE Access, 2019 As a typical variation of nonnegative matrix factorization (NMF), symmetric NMF (SNMF) is capable of exploiting information of the cluster embedded in the matrix of similarity.
Wei Yan +3 more
doaj +1 more source