Results 21 to 30 of about 1,708,415 (229)

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

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

Nonnegative Matrix Factorizations Performing Object Detection and Localization

Applied Computational Intelligence and Soft Computing, 2012
We study the problem of detecting and localizing objects in still, gray-scale images making use of the part-based representation provided by nonnegative matrix factorizations.
G. Casalino, N. Del Buono, M. Minervini
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

NIMFA: A Python Library for Nonnegative Matrix Factorization [PDF]

, 2012
NIMFA is an open-source Python library that provides a unified interface to nonnegative matrix factorization algorithms. It includes implementations of state-of-the-art factorization methods, initialization approaches, and quality scoring.
Zupan, Blaz, Zitnik, Marinka
core   +1 more source

Speech Enhancement Control Design Algorithm for Dual-Microphone Systems Using β-NMF in a Complex Environment

Complexity, 2018
Single-microphone speech enhancement algorithms by using nonnegative matrix factorization can only utilize the temporal and spectral diversity of the received signal, making the performance of the noise suppression degrade rapidly in a complex ...
Dong-xia Wang, Mao-song Jiang, Fang-lin Niu, Yu-dong Cao, Cheng-xu Zhou   +4 more
doaj   +1 more source

Symmetric Nonnegative Matrix Trifactorization [PDF]

, 2022
The Symmetric Nonnegative Matrix Trifactorization (SN-Trifactorization) is a factorization of an $n \times n$ nonnegative symmetric matrix $A$ of the form $BCB^T$, where $C$ is a $k \times k$ symmetric matrix, and both $B$ and $C$ are required to be ...
Bukovšek, Damjana Kokol, Šmigoc, Helena, Helena Šmigoc, Damjana Kokol Bukovšek, Kokol-Bukovšek, Damjana   +4 more
core   +1 more source

Collaborative filtering based on nonnegative/binary matrix factorization

Frontiers in Big Data
Collaborative filtering generates recommendations by exploiting user-item similarities based on rating data, which often contains numerous unrated items.
Yukino Terui, Yuka Inoue, Yohei Hamakawa, Kosuke Tatsumura, Kazue Kudo, Kazue Kudo   +5 more
doaj   +1 more source

Adversarially-Trained Nonnegative Matrix Factorization

, 2021
International audienceWe consider an adversarially-trained version of the nonnegative matrix factorization, a popular latent dimensionality reduction technique.
Tan, Vincent, y F, Cai, Ting, Févotte, Cédric, Cedric Fevotte, Tan, Vincent,, Ting Cai, Vincent Y. F. Tan   +6 more
core   +1 more source

Discriminatively Constrained Semi-Supervised Multi-View Nonnegative Matrix Factorization with Graph Regularization

Big Data Mining and Analytics
Nonnegative Matrix Factorization (NMF) is one of the most popular feature learning technologies in the field of machine learning and pattern recognition. It has been widely used and studied in the multi-view clustering tasks because of its effectiveness.
Guosheng Cui, Ye Li, Jianzhong Li, Jianping Fan   +3 more
doaj   +1 more source