Results 71 to 80 of about 114,742 (232)
Non-negative matrix factorization with sparseness constraints
Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. Although it has successfully been applied in several applications, it does not always result in parts-based ...
Patrik O. Hoyer, Peter Dayan
core +1 more source
We study the sparse non-negative least squares (S-NNLS) problem. S-NNLS occurs naturally in a wide variety of applications where an unknown, non-negative quantity must be recovered from linear measurements. We present a unified framework for S-NNLS based
Fedorov, Igor +5 more
core +1 more source
Cytarabine is a key therapy for acute myeloid leukaemia (AML), but its efficacy is limited by the dNTPase SAMHD1, which hydrolyses its active metabolite. Screening nucleotide biosynthesis inhibitors revealed that IMPDH inhibitors selectively sensitise SAMHD1‐proficient AML cells to cytarabine.
Miriam Yagüe‐Capilla +9 more
wiley +1 more source
KOMPRESI DAN PENGENALAN CITRA WAJAH DENGAN PENDEKATAN NON-NEGATIVE MATRIX FACTORIZATION [PDF]
KOMPRESI DAN PENGENALAN CITRA WAJAH DENGAN PENDEKATAN NON-NEGATIVE MATRIX FACTORIZATION - Face recognition, kompresi, Non-negative Matrix Factorization, Principal Component Analysis, Eigenface, Computer ...
BENNY KURNIAWAN USODO, FICTOR +2 more
core
Keratin 19 (KRT19) is overexpressed in high‐grade serous ovarian cancer with high levels of Kallikrein‐related peptidases (KLK) 4–7 and is associated with poor survival. In vivo analyses demonstrate that elevated KRT19 increases peritoneal tumour burden.
Sophia Bielesch +13 more
wiley +1 more source
Robust Hierarchical Learning for Non-Negative Matrix Factorization With Outliers
Desirable properties of extensions of non-negative matrix factorization (NMF) include robustness in the presence of noises and outliers, ease of implementation, the guarantee of convergence, operation in an automatic fashion that trades off the balance ...
Yinan Li +4 more
doaj +1 more source
Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization [PDF]
The separability assumption (Donoho & Stodden, 2003; Arora et al., 2012) turns non-negative matrix factorization (NMF) into a tractable problem. Recently, a new class of provably-correct NMF algorithms have emerged under this assumption.
Kambadur, Prabhanjan +2 more
core
Somatic mutational landscape in von Hippel–Lindau familial hemangioblastoma
The causes of central nervous system (CNS) hemangioblastoma in Von Hippel–Lindau (vHL) disease are unclear. We used Whole Exome Sequencing (WES) on familial hemangioblastoma to investigate events that underlie tumor development. Our findings suggest that VHL loss creates a permissive environment for tumor formation, while additional alterations ...
Maja Dembic +5 more
wiley +1 more source
Primal-Dual Algorithms for Non-negative Matrix Factorization with the Kullback-Leibler Divergence [PDF]
Non-negative matrix factorization (NMF) approximates a given matrix as a product of two non-negative matrices. Multiplicative algorithms deliver reliable results, but they show slow convergence for high-dimensional data and may be stuck away from local ...
Bach, Francis, Yanez, Felipe
core +2 more sources
We have established a humanized orthotopic patient‐derived xenograft (Hu‐oPDX) mouse model of high‐grade serous ovarian cancer (HGSOC) that recapitulates human tumor–immune interactions. Using combined anti‐PD‐L1/anti‐CD73 immunotherapy, we demonstrate the model's improved biological relevance and enhanced translational value for preclinical ...
Luka Tandaric +10 more
wiley +1 more source

