Results 61 to 70 of about 82,948 (222)
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.
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Online Nonnegative Matrix Factorization With Outliers [PDF]
IEEE Transactions on Signal Processing, 2016 We propose a unified and systematic framework for performing online nonnegative matrix factorization in the presence of outliers. Our framework is particularly suited to large-scale data. We propose two solvers based on projected gradient descent and the alternating direction method of multipliers.
Zhao, Renbo, Tan, Vincent Y. F.
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Big Data Mining and AnalyticsNonnegative Matrix Factorization (NMF) is one of the most popular feature learning technologies in the field of machine learning and pattern recognition. It has been widely used and studied in the multi-view clustering tasks because of its effectiveness.
Guosheng Cui +3 more
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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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Robustness Analysis of Hottopixx, a Linear Programming Model for Factoring Nonnegative Matrices [PDF]
, 2013 Although nonnegative matrix factorization (NMF) is NP-hard in general, it has been shown very recently that it is tractable under the assumption that the input nonnegative data matrix is close to being separable (separability requires that all columns of
Gillis, Nicolas
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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
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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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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
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