Results 141 to 150 of about 1,698,574 (297)

Improved Graph-Regularized Discriminative Nonnegative Matrix Factorization for Semi-Supervised Clustering

IEEE Access
Nonnegative matrix factorization (NMF) is an effective dimensionality reduction and representation learning technique that captures the intrinsic structure of nonnegative data by learning low-dimensional, parts-based representations.
Xuzhu Shen, Jie Li
doaj   +1 more source

Log-based sparse nonnegative matrix factorization for data representation. [PDF]

Knowl Based Syst, 2022
Peng C, Zhang Y, Chen Y, Kang Z, Chen C, Cheng Q.   +5 more
europepmc   +1 more source

World Models for Robotic Manipulation: A Survey

SmartBot, EarlyView.
World models enable robots to anticipate how candidate actions may alter object configurations, contact states, and scene geometry before physical execution. This survey examines world models for robotic manipulation as action‐conditioned predictive systems and organizes the literature according to predicted representations, interfaces between ...
Fangyuan Wang, Ziyuan Wang, Guorui Pei, Mengshi Zhang, Canxi Liang, Jun Hu, Zhongxuan Li, Jinsong Wu, Ning Han, Zeqing Zhang, Jiaming Qi, Hongmin Wu, Shiyao Zhang, Pai Zheng, Jia Pan, David Navarro‐Alarcon, Sichao Liu, Peng Zhou   +17 more
wiley   +1 more source

Two-Dimensional Semi-Nonnegative Matrix Factorization for Clustering. [PDF]

Inf Sci (N Y), 2022
Peng C, Zhang Z, Chen C, Kang Z, Cheng Q.   +4 more
europepmc   +1 more source

Uncertainty and Contract Choice in Two‐Tier Labor Markets

Southern Economic Journal, EarlyView.
ABSTRACT We develop a search‐and‐matching model in which firms choose between one‐period temporary contracts and open‐ended permanent contracts after observing persistent match quality. Permanent jobs retain valuable matches by lowering effective job‐to‐job turnover, but expose firms to firing costs; temporary jobs permit costless non‐renewal and can ...
Shutao Cao, Enchuan Shao, Pedro Silos
wiley   +1 more source

A Constrained Sparse Algorithm for Nonnegative Matrix Factorization

工程科学与技术, 2015
:Aiming at the lack of sparseness of factorization matrix in the nonnegative matrix factorization (NMF) algorithm,a new constrained NMF algorithm was proposed.A sparseness constraint was added to the original nonnegative matrix factorization (NMF ...
李臣明, 张师明, 李昌利
doaj  

Nonnegative matrix factorization analysis and multiple machine learning methods identified IL17C and ACOXL as novel diagnostic biomarkers for atherosclerosis. [PDF]

BMC Bioinformatics, 2023
Rao L, Peng B, Li T.
europepmc   +1 more source

The totally nonnegative completion problem

, 1998
An n-by-n real matrix is said to be totally positive (nonnegative) if every minor (principal and non-principal) is positive (nonnegative). The totally nonnegative completion problem asks which partially totally nonnegative matrices have a completion to a
Johnson, Charles R, Kroschel, Brenda K, Lundquist, Michael, Michael Lundquist, Charles Johnson, Brenda Kroschel   +5 more
core   +1 more source

Boosted unsupervised feature selection for tumor gene expression profiles

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract In an unsupervised scenario, it is challenging but essential to eliminate noise and redundant features for tumour gene expression profiles. However, the current unsupervised feature selection methods treat all samples equally, which tend to learn discriminative features from simple samples.
Yifan Shi, Kaixiang Yang, Mengzhi Wang, Zhiwen Yu, Huanqiang Zeng, Yang Hu   +5 more
wiley   +1 more source

Enhanced Extraction of Blood and Tissue Time-Activity Curves in Cardiac Mouse FDG PET Imaging by Means of Constrained Nonnegative Matrix Factorization. [PDF]

Int J Biomed Imaging, 2023
Sarrhini O, D'Orléans-Juste P, Rousseau JA, Beaudoin JF, Lecomte R.   +4 more
europepmc   +1 more source