Results 51 to 60 of about 1,630,238 (295)
Factorization of Matrix Polynomials with Symmetries [PDF]
SIAM Journal on Matrix Analysis and Applications, 1994 This paper presents a detailed study of the factorizations of matrix polynomials with symmetries. It begins with defining the key properties of matrix polynomials to be discussed: selfadjoint, symmetric, general rank, generally invertible, etc. Then representations of factorizations of various matrix polynomials are presented in detail.
André C. M. Ran, Leiba Rodman
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Guided Semi-Supervised Non-Negative Matrix Factorization
Algorithms, 2022 Classification and topic modeling are popular techniques in machine learning that extract information from large-scale datasets. By incorporating a priori information such as labels or important features, methods have been developed to perform ...
Pengyu Li +6 more
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Complexity, 2018 We present a novel method, called graph sparse nonnegative matrix factorization, for dimensionality reduction. The affinity graph and sparse constraint are further taken into consideration in nonnegative matrix factorization and it is shown that the ...
Xiangguang Dai +2 more
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Non-negative Matrix Factorization Parallel Optimization Algorithm Based on Lp-norm [PDF]
Jisuanji kexueNon-negative matrix factorization algorithm is an important tool for image clustering,data compression and feature extraction.Traditional non-negative matrix factorization algorithms mostly use Euclidean distance to measure reconstruction error,which has
HUANG Lulu, TANG Shuyu, ZHANG Wei, DAI Xiangguang
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Stochastic Matrix Factorization [PDF]
SSRN Electronic Journal, 2016 24 pages, 4 figures, 5 ...
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Optimizing and Factorizing the Wilson Matrix
The American Mathematical Monthly, 2022 The Wilson matrix, W, is a 4 × 4 unimodular symmetric positive definite matrix of integers that has been used as a test matrix since the 1940’s, owing to its mild ill-conditioning. We ask how close W is to being the most ill-conditioned matrix in its class, with or without the requirement of positive definiteness.
Nicholas J. Higham +1 more
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Banach Spaces of Analytic Vector-valued Functions [PDF]
, 2007 The main theme of the thesis is the study of continuity and approximation problems, involving matrix-valued and vector-valued Hardy spaces on the unit disc ID and its boundary T in the complex plane.
Barclay, Steven John
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Personalization Recommendation Algorithm Based on Trust Correlation Degree and Matrix Factorization
IEEE Access, 2019 The rapid development of the Internet of Things (IoT) and e-commerce has brought a lot of convenience to people's lives. IoT applications generate a large number of services and user data.
Weimin Li +6 more
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Transductive Nonnegative Matrix Tri-Factorization
IEEE Access, 2020 Nonnegative matrix factorization (NMF) decomposes a nonnegative matrix into the product of two lower-rank nonnegative matrices. Since NMF learns parts-based representation, it has been widely used as a feature learning component in many fields.
Xiao Teng +4 more
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Sparse Deep Nonnegative Matrix Factorization
Big Data Mining and Analytics, 2020 Nonnegative Matrix Factorization (NMF) is a powerful technique to perform dimension reduction and pattern recognition through single-layer data representation learning. However, deep learning networks, with their carefully designed hierarchical structure,
Zhenxing Guo, Shihua Zhang
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