منابع مشابه
Non-Negative Matrix Factorizations for Multiplex Network Analysis
Networks have been a general tool for representing, analyzing, and modeling relational data arising in several domains. One of the most important aspect of network analysis is community detection or network clustering. Until recently, the major focus have been on discovering community structure in single (i.e., monoplex) networks. However, with the advent of relational data with multiple modali...
متن کاملMotivating Non - Negative Matrix Factorizations ∗
Given a vector space model encoding of a large data set, a usual starting point for data analysis is rank reduction [1]. However, standard rank reduction techniques such as the QR, Singular Value (SVD), and Semi-Discrete (SDD) decompositions and Principal Component Analysis (PCA) produce low rank bases which do not respect the non-negativity or structure of the original data. Non-negative Matri...
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MOTIVATION Many practical pattern recognition problems require non-negativity constraints. For example, pixels in digital images and chemical concentrations in bioinformatics are non-negative. Sparse non-negative matrix factorizations (NMFs) are useful when the degree of sparseness in the non-negative basis matrix or the non-negative coefficient matrix in an NMF needs to be controlled in approx...
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In this work we apply non-negative matrix factorizations (NMF) to some imaging and inverse problems. We propose a sparse low-rank approximation of big data and images in terms of tensor products, and investigate its effectiveness in terms of the number of tensor products to be used in the approximation. A multi-resolution analysis (MRA) framework is presented using a sparse low-rank approximati...
متن کاملComputing non-negative tensor factorizations
Nonnegative tensor factorization (NTF) is a technique for computing a parts-based representation of high-dimensional data. NTF excels at exposing latent structures in datasets, and at finding good low-rank approximations to the data. We describe an approach for computing the NTF of a dataset that relies only on iterative linear-algebra techniques and that is comparable in cost to the nonnegativ...
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ژورنال
عنوان ژورنال: IEEE Transactions on Pattern Analysis and Machine Intelligence
سال: 2019
ISSN: 0162-8828,2160-9292,1939-3539
DOI: 10.1109/tpami.2018.2821146