Results 31 to 40 of about 13,782,934 (217)

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

Approximate L0 constrained non-negative matrix and tensor factorization [PDF]

2008 IEEE International Symposium on Circuits and Systems (ISCAS), 2008
Non-negative matrix factorization (NMF), i.e. V ap WH where both V, W and H are non-negative has become a widely used blind source separation technique due to its part based representation. The NMF decomposition is not in general unique and a part based representation not guaranteed.
Morten Mørup, Kristoffer Hougaard Madsen, Lars Kai Hansen   +2 more
openaire   +1 more source

Sparse General Non-Negative Matrix Factorization Based on Left Semi-Tensor Product

IEEE Access, 2019
The dimension reduction of large scale high-dimensional data is a challenging task, especially the dimension reduction of face data and the accuracy increment of face recognition in the large scale face recognition system, which may cause large storage ...
Zigang Chen, Lixiang Li, Haipeng Peng, Yuhong Liu, Haihua Zhu, Yixian Yang   +5 more
doaj   +1 more source

Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains. [PDF]

PLoS Computational Biology, 2016
Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in ...
Arno Onken, Jian K Liu, P P Chamanthi R Karunasekara, Ioannis Delis, Tim Gollisch, Stefano Panzeri   +5 more
doaj   +1 more source

Application of Non-Negative Tensor Factorization for Airport Flight Delay Pattern Recognition

IEEE Access, 2019
With the rapid development of civil aviation transportation in China, huge demand growth has broken the balance between supply and demand, resulting in airspace congestion and increasing flight delays.
Han Zhong, Geqi Qi, Wei Guan, Xiaochen Hua   +3 more
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

Low-Rank Tensor Decomposition With Smooth and Sparse Regularization for Hyperspectral and Multispectral Data Fusion

IEEE Access, 2020
The fusion of hyperspectral and multispectral images is an effective way to obtain hyperspectral super-resolution images with high spatial resolution. A hyperspectral image is a datacube containing two spatial dimensions and a spectral dimension.
Fei Ma, Feixia Yang, Yanwei Wang
doaj   +1 more source

Non-negative Factorization of the Occurrence Tensor from Financial Contracts

CoRR, 2016
We propose an algorithm for the non-negative factorization of an occurrence tensor built from heterogeneous networks. We use l0 norm to model sparse errors over discrete values (occurrences), and use decomposed factors to model the embedded groups of nodes. An efficient splitting method is developed to optimize the nonconvex and nonsmooth objective. We
Zheng Xu 0002, Furong Huang, Louiqa Raschid, Tom Goldstein   +3 more
openaire   +3 more sources

Navigating the Functional Landscape of Transcription Factors via Non-Negative Tensor Factorization Analysis of MEDLINE Abstracts

Frontiers in Bioengineering and Biotechnology, 2017
In this study, we developed and evaluated a novel text-mining approach, using non-negative tensor factorization (NTF), to simultaneously extract and functionally annotate transcriptional modules consisting of sets of genes, transcription factors (TFs ...
Sujoy Roy, Sujoy Roy, Daqing Yun, Behrouz Madahian, Michael W. Berry, Lih-Yuan Deng, Daniel Goldowitz, Ramin Homayouni, Ramin Homayouni, Ramin Homayouni   +9 more
doaj   +1 more source

Pre-seismic geomagnetic fusion anomaly extraction based on Spatially Weighted Non-negative Tensor Factorization [PDF]

Natural Hazards and Earth System Sciences
Earthquake preparation processes are known to generate geomagnetic anomalies in some cases. Existing methods for extracting pre-seismic geomagnetic anomalies from multi-station observations are limited by the lack of physically meaningful constraints ...
B. Yang, K. Zhu, T. Wang, D. Zhang, W. Chen, Y. Zhang, P. Wang, X. Li, Y. Cheng   +8 more
doaj   +1 more source