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Online Learning for Matrix Factorization and Sparse Coding
Journal of machine learning research, 2009Sparse 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
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, 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
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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
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Factoring Effectiveness Factors!
Journal of the Operational Research Society, 1990It has previously been suggested that the effectiveness of strategic planning systems may be characterized in terms of a multi-attribute framework. This paper explores the possibility of reducing the postulated set of attributes to an ‘irreducible core’ by means of a factor analysis.
A. R. Lock, M. J. Foster
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Smooth stabilization implies coprime factorization
IEEE Transactions on Automatic Control, 1989It 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
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Factorization Algebras in Quantum Field Theory
, 2021Factorization 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
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Fusing Hyperspectral and Multispectral Images via Coupled Sparse Tensor Factorization
IEEE Transactions on Image Processing, 2018Fusing 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 +3 more
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Factors and factors of personality.
Psychological Bulletin, 1975An effort was made to account for the diverse sets of factors of personality found by the analysis of questionnaire items as reported by different investigators and to see what common ground there might be. Divergencies were attributed to certain insufficiencies in factor analysis and to the fundamental views of analysts with regard to emphasis upon ...
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Scientific American, 2014
The article focuses on the physiological and cognitive differences between humans and chimpanzees. Topics include how Homo sapiens became the dominant species, how human behavior differs from the behavior of apes, and the link between language and human evolution. Information is provided on the brain size differences between humans and chimpanzees.
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The article focuses on the physiological and cognitive differences between humans and chimpanzees. Topics include how Homo sapiens became the dominant species, how human behavior differs from the behavior of apes, and the link between language and human evolution. Information is provided on the brain size differences between humans and chimpanzees.
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Semi-Orthogonal Low-Rank Matrix Factorization for Deep Neural Networks
Interspeech, 2018Time 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 +6 more
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