Results 51 to 60 of about 32,711 (308)
Adaptive Graph Regularization Discriminant Nonnegative Matrix Factorization for Data Representation
IEEE Access, 2019 Nonnegative matrix factorization, as a classical part-based representation method, has been widely used in pattern recognition, data mining and other fields.
Lin Zhang +3 more
doaj +1 more source
Journal of Statistical Theory and Applications (JSTA), 2020 The Probabilistic Latent Semantic Analysis has been related with the Singular Value Decomposition. Several problems occur when this comparative is done.
Pau Figuera Vinué +1 more
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A Symmetric Rank-one Quasi Newton Method for Non-negative Matrix Factorization [PDF]
, 2013 As we all known, the nonnegative matrix factorization (NMF) is a dimension reduction method that has been widely used in image processing, text compressing and signal processing etc.
Lai, Shu-Zhen +2 more
core +3 more sources
Reverse annealing for nonnegative/binary matrix factorization.
PLoS ONE, 2021 It was recently shown that quantum annealing can be used as an effective, fast subroutine in certain types of matrix factorization algorithms. The quantum annealing algorithm performed best for quick, approximate answers, but performance rapidly ...
John Golden, Daniel O'Malley
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Deep Nonnegative Dictionary Factorization for Hyperspectral Unmixing
Remote Sensing, 2020 As a powerful blind source separation tool, Nonnegative Matrix Factorization (NMF) with effective regularizations has shown significant superiority in spectral unmixing of hyperspectral remote sensing images (HSIs) owing to its good physical ...
Wenhong Wang, Hongfu Liu
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Optimization of identifiability for efficient community detection
New Journal of Physics, 2020 Many physical and social systems are best described by networks. And the structural properties of these networks often critically determine the properties and function of the resulting mathematical models.
Hui-Jia Li +3 more
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Fast and Robust Recursive Algorithms for Separable Nonnegative Matrix Factorization [PDF]
, 2013 In this paper, we study the nonnegative matrix factorization problem under the separability assumption (that is, there exists a cone spanned by a small subset of the columns of the input nonnegative data matrix containing all columns), which is ...
Gillis, Nicolas, Vavasis, Stephen A.
core +2 more sources
Quantum‐Grade Nanodiamonds from a Single‐Step, Industrial‐Scale Pressure and Temperature Process
Advanced Functional Materials, EarlyView.Novel method for creation of nitrogen‐vacancy centers in 50‐nm nanodiamonds based on high‐temperature plastic deformation is demonstrated. Compared to the electron irradiation approach, it yields nitrogen‐vacancy centers with significantly improved charge stability, T1 relaxation time, and optical Rabi contrast.
Yahua Bao +17 more
wiley +1 more source
Latent Multi-View Semi-Nonnegative Matrix Factorization with Block Diagonal Constraint
Axioms, 2022 Multi-view clustering algorithms based on matrix factorization have gained enormous development in recent years. Although these algorithms have gained impressive results, they typically neglect the spatial structures that the latent data representation ...
Lin Yuan +3 more
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Algorithms for Positive Semidefinite Factorization
, 2017 This paper considers the problem of positive semidefinite factorization (PSD factorization), a generalization of exact nonnegative matrix factorization. Given an $m$-by-$n$ nonnegative matrix $X$ and an integer $k$, the PSD factorization problem consists
Gillis, Nicolas +2 more
core +1 more source