Results 101 to 110 of about 2,535,217 (348)
A multilevel approach for nonnegative matrix factorization [PDF]
Journal of Computational and Applied Mathematics, 2012 Nonnegative Matrix Factorization (NMF) is the problem of approximating a nonnegative matrix with the product of two low-rank nonnegative matrices and has been shown to be particularly useful in many applications, e.g., in text mining, image processing, computational biology, etc. In this paper, we explain how algorithms for NMF can be embedded into the
Nicolas Gillis, François Glineur
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Irrigation and Drainage, EarlyView.ABSTRACT This study develops an integrated simulation–optimization framework for sustainable crop allocation and water resource management in the Bargarh Canal Command (BCC), eastern India. Efficient irrigation allocation remains a critical challenge due to competing demands, groundwater–surface water interactions and environmental constraints ...
Priyanka Mohapatra +2 more
wiley +1 more source
Discrete Dynamics in Nature and Society, 2009 The original Hopfield neural networks model is adapted so that the weights of the resulting network are time varying. In this paper, the Discrete Hopfield neural networks with weight function matrix (DHNNWFM) the weight changes with time, are considered,
Jun Li +3 more
doaj +1 more source
Efficient First‐Principles Inverse Design of Nanolasers
Laser &Photonics Reviews, EarlyView.This article introduces a first‐principles inverse‐design framework for nanolasers that directly incorporates nonlinear lasing physics. By unifying steady‐state ab‐initio laser theory (SALT) with topology optimization, it reveals how spatial hole burning, gain saturation, and cavity‐emitter coupling shape laser performance, enabling efficient discovery
Beñat Martinez de Aguirre Jokisch +5 more
wiley +1 more source
Using underapproximations for sparse nonnegative matrix factorization [PDF]
Nonnegative Matrix Factorization (NMF) has gathered a lot of attention in the last decade and has been successfully applied in numerous applications.
GILLIS, Nicolas, GLINEUR, François
core
Nonnegative square roots of matrices
, 2016 By the square root of a (square) matrix A we mean a matrix B that satisfies B2=A. In this paper, we begin a study of the (entrywise) nonnegative square roots of nonnegative matrices, adopting mainly a graph-theoretic approach.
Bit-ShunTam;Peng-RueiHuang
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Fast Parallel Randomized Algorithm for Nonnegative Matrix Factorization with KL Divergence for Large Sparse Datasets [PDF]
, 2016 Nonnegative Matrix Factorization (NMF) with Kullback-Leibler Divergence (NMF-KL) is one of the most significant NMF problems and equivalent to Probabilistic Latent Semantic Indexing (PLSI), which has been successfully applied in many applications.
Ho, Tu-Bao, Nguyen, Duy-Khuong
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Mathematical Methods in the Applied Sciences, EarlyView.A highly accurate numerical method is given for the solution of boundary value problem of generalized Bagley‐Torvik (BgT) equation with Caputo derivative of order 0<β<2$$ 0<\beta <2 $$ by using the collocation‐shooting method (C‐SM). The collocation solution is constructed in the space Sm+1(1)$$ {S}_{m+1}^{(1)} $$ as piecewise polynomials of degree at ...
Suzan Cival Buranay +2 more
wiley +1 more source
Discriminative Multiview Nonnegative Matrix Factorization for Classification
IEEE Access, 2019 Multiview nonnegative matrix has shown many promising applications in computer vision and pattern recognition. However, most existing works focus on view consistency and ignore discrimination.
Weihua Ou +4 more
doaj +1 more source
Nonnegative factorization and the maximum edge biclique problem [PDF]
Nonnegative matrix factorization (NMF) is a data analysis technique based on the approximation of a nonnegative matrix with a product of two nonnegative factors, which allows compression and interpretation of nonnegative data. In this paper, we study the
GILLIS, Nicolas, GLINEUR, François
core