Results 21 to 30 of about 1,983,602 (251)

Uncovering community structures with initialized Bayesian nonnegative matrix factorization. [PDF]

PLoS ONE, 2014
Uncovering community structures is important for understanding networks. Currently, several nonnegative matrix factorization algorithms have been proposed for discovering community structure in complex networks.
Xianchao Tang, Tao Xu, Xia Feng, Guoqing Yang   +3 more
doaj   +1 more source

Simultaneous non-negative matrix factorization for multiple large scale gene expression datasets in toxicology [PDF]

, 2012
Non-negative matrix factorization is a useful tool for reducing the dimension of large datasets. This work considers simultaneous non-negative matrix factorization of multiple sources of data.
Clare M. Lee, Vass J. Keith, D R Haggart, Lee Clare M., Mudaliar, MAV, Higham, Desmond, Vass, D.J., Manikhandan A V Mudaliar, Gino Miele, Mudaliar, Manikhandan A.V., Haggart, D. R., Mudaliar, M.A.V., Higham, Desmond J., Haggart D. R., Crowther, Daniel, D. R. Haggart, Lee, C.M., Lee, Clare M., Mudaliar Manikhandan A. V., J Keith Vass, Higham Desmond J., Wolf, C.R., Higham, D.J., Wolf C. Roland, Miele Gino, Mudaliar, Manikhandan A. V., Miele, Geno, Desmond J Higham, Clare M Lee, C. Roland Wolf, Miele, G., Manikhandan A. V. Mudaliar, C Roland Wolf, Crowther Daniel, Vass, J.K., Miele, Gino, J. Keith Vass, Crowther, D., Crowther, Daniel; id_orcid, Daniel Crowther, Vass, J. Keith, Desmond J. Higham, Haggart, D.R., Wolf, C. Roland, Lee, Clare   +44 more
core   +1 more source

Simultaneous non-negative matrix factorization for multiple large scale gene expression datasets in toxiciology [PDF]

, 2012
Non-negative matrix factorization is a useful tool for reducing the dimension of large datasets. This work considers simultaneous non-negative matrix factorization of multiple sources of data.
Mudaliar, Manikhandan A. V., Miele, Geno, Higham, Desmond J., Crowther, Daniel, Lee, Clare M., Vass, J. Keith, Haggart, D.R., Wolf, C. Roland   +7 more
core   +2 more sources

Face Recognition Based on Wavelet Kernel Non-Negative Matrix Factorization

Cybernetics and Information Technologies, 2014
In this paper a novel face recognition algorithm, based on wavelet kernel non-negative matrix factorization (WKNMF), is proposed. By utilizing features from multi-resolution analysis, the nonlinear mapping capability of kernel nonnegative matrix ...
Bai, Lin, Li Yanbo, Hui Meng
doaj   +1 more source

Graph regularized non-negative matrix factorization with prior knowledge consistency constraint for drug–target interactions prediction

BMC Bioinformatics, 2022
Background Identifying drug–target interactions (DTIs) plays a key role in drug development. Traditional wet experiments to identify DTIs are expensive and time consuming. Effective computational methods to predict DTIs are useful to narrow the searching
Junjun Zhang, Minzhu Xie
doaj   +1 more source

Graph Sparse Nonnegative Matrix Factorization Algorithm Based on the Inertial Projection Neural Network

Complexity, 2018
We present a novel method, called graph sparse nonnegative matrix factorization, for dimensionality reduction. The affinity graph and sparse constraint are further taken into consideration in nonnegative matrix factorization and it is shown that the ...
Xiangguang Dai, Chuandong Li, Biqun Xiang   +2 more
doaj   +1 more source

Evolving Matrix-Factorization-Based Collaborative Filtering Using Genetic Programming

Applied Sciences, 2020
Recommender systems aim to estimate the judgment or opinion that a user might offer to an item. Matrix-factorization-based collaborative filtering typifies both users and items as vectors of factors inferred from item rating patterns.
Raúl Lara-Cabrera, Ángel González-Prieto, Fernando Ortega, Jesús Bobadilla   +3 more
doaj   +1 more source

Non-negative Matrix Factorization Parallel Optimization Algorithm Based on Lp-norm [PDF]

Jisuanji kexue
Non-negative matrix factorization algorithm is an important tool for image clustering,data compression and feature extraction.Traditional non-negative matrix factorization algorithms mostly use Euclidean distance to measure reconstruction error,which has
HUANG Lulu, TANG Shuyu, ZHANG Wei, DAI Xiangguang
doaj   +1 more source

Robust Exponential Graph Regularization Non-Negative Matrix Factorization Technology for Feature Extraction

Mathematics, 2023
Graph regularized non-negative matrix factorization (GNMF) is widely used in feature extraction. In the process of dimensionality reduction, GNMF can retain the internal manifold structure of data by adding a regularizer to non-negative matrix ...
Minghua Wan, Mingxiu Cai, Guowei Yang
doaj   +1 more source

Categorical Dimensions of Human Odor Descriptor Space Revealed by Non-Negative Matrix Factorization [PDF]

, 2013
In contrast to most other sensory modalities, the basic perceptual dimensions of olfaction remain unclear. Here, we use non-negative matrix factorization (NMF) – a dimensionality reduction technique – to uncover structure in a panel of odor profiles ...
Castro, Jason B., Jason B. Castro, Castro, Jason B, Chennubhotla, Chakra S., Ramanathan, Arvind, Schaefer, Andreas, Chennubhotla Chakra S., Arvind Ramanathan (198127), Jason B. Castro (460485), Jason B Castro, Ramanathan Arvind, Arvind Ramanathan, Castro Jason B., Chakra S. Chennubhotla, Chennubhotla, Chakra S, Chakra S Chennubhotla, Chakra S. Chennubhotla (232086)   +16 more
core   +2 more sources