Results 291 to 300 of about 406,461 (313)

Improving drug repositioning accuracy using non-negative matrix tri-factorization. [PDF]

Sci Rep
Li Q, Wang Y, Wang J, Zhao C.
europepmc   +1 more source

iTissue

Zambrana C, Malod-Dognin N, Pržulj N.
europepmc   +1 more source

Next-to-leading order evolution of structure functions without PDFs. [PDF]

Eur Phys J C Part Fields
Lappi T, Mäntysaari H, Paukkunen H, Tevio M.   +3 more
europepmc   +1 more source

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Online Learning for Matrix Factorization and Sparse Coding

Journal of machine learning research, 2009
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics.
J. Mairal, F. Bach, J. Ponce, G. Sapiro
semanticscholar   +1 more source

Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values†

, 1994
A new variant ‘PMF’ of factor analysis is described. It is assumed that X is a matrix of observed data and σ is the known matrix of standard deviations of elements of X. Both X and σ are of dimensions n × m.
P. Paatero, U. Tapper
semanticscholar   +1 more source

Smooth stabilization implies coprime factorization

IEEE Transactions on Automatic Control, 1989
It is shown that coprime right factorizations exist for the input-to-state mapping of a continuous-time nonlinear system provided that the smooth feedback stabilization problem is solvable for this system.
Eduardo Sontag
semanticscholar   +1 more source

Factorization Algebras in Quantum Field Theory

, 2021
Factorization algebras are local-to-global objects that play a role in classical and quantum field theory that is similar to the role of sheaves in geometry: they conveniently organize complicated information.
K. Costello, Owen Gwilliam
semanticscholar   +1 more source

Fusing Hyperspectral and Multispectral Images via Coupled Sparse Tensor Factorization

IEEE Transactions on Image Processing, 2018
Fusing a low spatial resolution hyperspectral image (LR-HSI) with a high spatial resolution multispectral image (HR-MSI) to obtain a high spatial resolution hyperspectral image (HR-HSI) has attracted increasing interest in recent years. In this paper, we
Shutao Li, Renwei Dian, Leyuan Fang, J. Bioucas-Dias   +3 more
semanticscholar   +1 more source

Semi-Orthogonal Low-Rank Matrix Factorization for Deep Neural Networks

Interspeech, 2018
Time Delay Neural Networks (TDNNs), also known as one-dimensional Convolutional Neural Networks (1-d CNNs), are an efficient and well-performing neural network architecture for speech recognition.
Daniel Povey, Gaofeng Cheng, Yiming Wang, Ke Li, Hainan Xu, M. Yarmohammadi, S. Khudanpur   +6 more
semanticscholar   +1 more source