Results 51 to 60 of about 142,276 (359)
A deep matrix factorization method for learning attribute representations [PDF]
, 2015 Semi-Non-negative Matrix Factorization is a technique that learns a low-dimensional representation of a dataset that lends itself to a clustering interpretation. It is possible that the mapping between this new representation and our original data matrix
Bousmalis, Konstantinos +3 more
core +3 more sources
Quaternion Non-negative Matrix Factorization: definition, uniqueness and algorithm
, 2020 This article introduces quaternion non-negative matrix factorization (QNMF), which generalizes the usual non-negative matrix factorization (NMF) to the case of polarized signals.
Brie, David +2 more
core +3 more sources
Semi-Supervised Projective Non-Negative Matrix Factorization for Cancer Classification. [PDF]
PLoS ONE, 2015 Advances in DNA microarray technologies have made gene expression profiles a significant candidate in identifying different types of cancers. Traditional learning-based cancer identification methods utilize labeled samples to train a classifier, but they
Xiang Zhang +4 more
doaj +1 more source
A Symmetric Rank-one Quasi Newton Method for Non-negative Matrix Factorization [PDF]
, 2013 As we all known, the nonnegative matrix factorization (NMF) is a dimension reduction method that has been widely used in image processing, text compressing and signal processing etc.
Lai, Shu-Zhen +2 more
core +3 more sources
Reciprocal control of viral infection and phosphoinositide dynamics
FEBS Letters, EarlyView.Phosphoinositides, although scarce, regulate key cellular processes, including membrane dynamics and signaling. Viruses exploit these lipids to support their entry, replication, assembly, and egress. The central role of phosphoinositides in infection highlights phosphoinositide metabolism as a promising antiviral target.
Marie Déborah Bancilhon, Bruno Mesmin
wiley +1 more source
Fast optimization of non-negative matrix tri-factorization.
PLoS ONE, 2019 Non-negative matrix tri-factorization (NMTF) is a popular technique for learning low-dimensional feature representation of relational data. Currently, NMTF learns a representation of a dataset through an optimization procedure that typically uses ...
Andrej Čopar +2 more
doaj +1 more source
FEBS Letters, EarlyView.Fluorescent probes allow dynamic visualization of phosphoinositides in living cells (left), whereas mass spectrometry provides high‐sensitivity, isomer‐resolved quantitation (right). Their synergistic use captures complementary aspects of lipid signaling. This review illustrates how these approaches reveal the spatiotemporal regulation and quantitative
Hiroaki Kajiho +3 more
wiley +1 more source
A Non-monotone Alternating Updating Method for A Class of Matrix Factorization Problems
, 2018 In this paper we consider a general matrix factorization model which covers a large class of existing models with many applications in areas such as machine learning and imaging sciences.
Chen, Xiaojun, Pong, Ting Kei, Yang, Lei
core +1 more source
ACCOUNTING FOR PHASE CANCELLATIONS IN NON-NEGATIVE MATRIX FACTORIZATION USING WEIGHTED DISTANCES [PDF]
, 2014 (c)2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or ...
Ewert, S, IEEE, Plumbley, MD, Sandler, M
core +1 more source
An intracellular transporter mitigates the CO2‐induced decline in iron content in Arabidopsis shoots
FEBS Letters, EarlyView.This study identifies a gene encoding a transmembrane protein, MIC, which contributes to the reduction of shoot Fe content observed in plants under elevated CO2. MIC is a putative Fe transporter localized to the Golgi and endosomal compartments. Its post‐translational regulation in roots may represent a potential target for improving plant nutrition ...
Timothy Mozzanino +7 more
wiley +1 more source