Results 1 to 10 of about 142,276 (359)

Discriminant projective non-negative matrix factorization. [PDF]

PLoS ONE, 2013
Projective non-negative matrix factorization (PNMF) projects high-dimensional non-negative examples X onto a lower-dimensional subspace spanned by a non-negative basis W and considers W(T) X as their coefficients, i.e., X≈WW(T) X.
Naiyang Guan, Xiang Zhang, Zhigang Luo, Dacheng Tao, Xuejun Yang   +4 more
doaj   +10 more sources

Co-sparse Non-negative Matrix Factorization [PDF]

Frontiers in Neuroscience, 2022
Non-negative matrix factorization, which decomposes the input non-negative matrix into product of two non-negative matrices, has been widely used in the neuroimaging field due to its flexible interpretability with non-negativity property.
Fan Wu, Jiahui Cai, Canhong Wen, Haizhu Tan   +3 more
doaj   +6 more sources

Non-negative Matrix Factorization: A Survey [PDF]

The Computer Journal, 2021
Non-negative matrix factorization (NMF) is a powerful tool for data science researchers, and it has been successfully applied to data mining and machine learning community, due to its advantages such as simple form, good interpretability and less ...
Jiangzhang Gan, Tong Liu, Li Li, Jilian Zhang   +3 more
semanticscholar   +4 more sources

Shifted Non-negative Matrix Factorization [PDF]

2007 IEEE Workshop on Machine Learning for Signal Processing, 2007
Non-negative matrix factorization (NMF) has become a widely used blind source separation technique due to its part based representation and ease of interpretability. We currently extend the NMF model to allow for delays between sources and sensors. This is a natural extension for spectrometry data where a shift in onset of frequency profile can be ...
Hansen, Lars Kai, Madsen, Kristoffer Hougaard, Mørup, Morten   +2 more
core   +5 more sources

Multi-constraint non-negative matrix factorization for community detection: orthogonal regular sparse constraint non-negative matrix factorization [PDF]

Complex & Intelligent Systems
Community detection is an important method to analyze the characteristics and structure of community networks, which can excavate the potential links between nodes and further discover subgroups from complex networks.
Zigang Chen, Qi Xiao, Tao Leng, Zhenjiang Zhang, Ding Pan, Yuhong Liu, Xiaoyong Li   +6 more
doaj   +2 more sources

Guided Semi-Supervised Non-Negative Matrix Factorization [PDF]

Algorithms, 2022
Classification and topic modeling are popular techniques in machine learning that extract information from large-scale datasets. By incorporating a priori information such as labels or important features, methods have been developed to perform ...
Pengyu Li, Christine Tseng, Yaxuan Zheng, Joyce A. Chew, Longxiu Huang, Benjamin Jarman, Deanna Needell   +6 more
doaj   +2 more sources

Parsing altered gray matter morphology of depression using a framework integrating the normative model and non-negative matrix factorization. [PDF]

Nat Commun, 2023
The high inter-individual heterogeneity in individuals with depression limits neuroimaging studies with case-control approaches to identify promising biomarkers for individualized clinical decision-making.
Han S, Cui Q, Zheng R, Li S, Zhou B, Fang K, Sheng W, Wen B, Liu L, Wei Y, Chen H, Chen Y, Cheng J, Zhang Y.   +13 more
europepmc   +2 more sources

Optimization and expansion of non-negative matrix factorization

BMC Bioinformatics, 2020
Background Non-negative matrix factorization (NMF) is a technique widely used in various fields, including artificial intelligence (AI), signal processing and bioinformatics.
Xihui Lin, Paul C. Boutros
doaj   +2 more sources

Truncated Cauchy Non-Negative Matrix Factorization [PDF]

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019
Non-negative matrix factorization (NMF) minimizes the euclidean distance between the data matrix and its low rank approximation, and it fails when applied to corrupted data because the loss function is sensitive to outliers.
Naiyang Guan, Tongliang Liu, Yangmuzi Zhang, D. Tao, L. Davis   +4 more
semanticscholar   +5 more sources

Rank selection for non‐negative matrix factorization [PDF]

Statistics in Medicine, 2022
Non‐Negative Matrix Factorization (NMF) is a widely used dimension reduction method that factorizes a non‐negative data matrix into two lower dimensional non‐negative matrices: one is the basis or feature matrix which consists of the variables and the ...
Yun Cai, Hong Gu, Toby Kenney
semanticscholar   +5 more sources