Results 81 to 90 of about 23,571 (300)

Hessian Regularization Based Factorization Algorithm Combining Multi-view and Non-negative Matrix [PDF]

open access: yesJisuanji gongcheng, 2017
Non-negative matrix does not consider the manifold of data when represents multi-view data,which results in the ineffective express of the data internal expression.In this paper,Hessian regularized Non-negative Matrix Factorization(NMF) is proposed.By ...
WANG Chaofeng,SHI Jun,WU Jinjie,ZHU Jie
doaj   +1 more source

EDNRB‐dependent endothelin signaling reduces proliferation and promotes proneural‐to‐mesenchymal transition in gliomas

open access: yesMolecular Oncology, EarlyView.
Glioma cells mainly express the endothelin receptor EDNRB, while EDNRA is restricted to a perivascular tumor subpopulation. Endothelin signaling reduces glioma cell proliferation while promoting migration and a proneural‐to‐mesenchymal transition associated with poor prognosis. This pathway activates Ca2+, K+, ERK, and STAT3 signalings and is regulated
Donovan Pineau   +36 more
wiley   +1 more source

Non-negative matrix factorization.

open access: yes, 2013
Non-negative matrix factorization.
Daniel Kaliski (336793)   +9 more
core   +1 more source

Topic supervised non-negative matrix factorization

open access: yesCoRR, 2017
Topic models have been extensively used to organize and interpret the contents of large, unstructured corpora of text documents. Although topic models often perform well on traditional training vs. test set evaluations, it is often the case that the results of a topic model do not align with human interpretation.
MacMillan, K., Wilson, James D
openaire   +2 more sources

IMPDH inhibition enhances cytarabine efficacy in SAMHD1‐expressing leukaemia cells via guanine nucleotide depletion

open access: yesMolecular Oncology, EarlyView.
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

Learning latent features with infinite non-negative binary matrix tri-factorization [PDF]

open access: yes, 2016
Non-negative Matrix Factorization (NMF) has been widely exploited to learn latent features from data. However, previous NMF models often assume a fixed number of features, saypfeatures, wherepis simply searched by experiments.
Hussain, Amir   +7 more
core   +1 more source

Enforced Sparse Non-negative Matrix Factorization [PDF]

open access: yes2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2016
Non-negative matrix factorization (NMF) is a dimensionality reduction algorithm for data that can be represented as an undirected bipartite graph. It has become a common method for generating topic models of text data because it is known to produce good results, despite its relative simplicity of implementation and ease of computation.
Brendan Gavin   +2 more
openaire   +1 more source

Keratin 19 as a prognostic marker and contributing factor of metastasis and chemoresistance in high‐grade serous ovarian cancer

open access: yesMolecular Oncology, EarlyView.
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 capped norm dual hyper-graph regularized non-negative matrix tri-factorization

open access: yes, 2023
Non-negative matrix factorization (NMF) has been widely used in machine learning and data mining fields. As an extension of NMF, non-negative matrix tri-factorization (NMTF) provides more degrees of freedom than NMF.
Baicheng Pan (16678341)   +3 more
core  

Muscle Synergy during Wrist Movements Based on Non-Negative Tucker Decomposition

open access: yesSensors
Modular control of the muscle, which is called muscle synergy, simplifies control of the movement by the central nervous system. The purpose of this study was to explore the synergy in both the frequency and movement domains based on the non-negative ...
Xiaoling Chen   +5 more
doaj   +1 more source

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