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Algorithms for non-negative matrix factorization

D Seung, +1 more
- Vol. 13, pp 556-562
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The article was published on 2001-01-01 and is currently open access. It has received 5015 citations till now. The article focuses on the topics: Non-negative matrix factorization.

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Proceedings ArticleDOI

On trivial solution and scale transfer problems in graph regularized NMF

TL;DR: A Normalized Cut-like constraint is imposed on the cluster assignment matrix to make the optimization problem well-defined, and a multiplicative updating algorithm is derived that can be applied for document clustering and co-clustering respectively.
Journal ArticleDOI

Editorial: Music genre classification based on local feature selection using a self-adaptive harmony search algorithm

TL;DR: An automatic music genre-classification system based on a local feature-selection strategy by using a self-adaptive harmony search (SAHS) algorithm that shows that the local-selection strategies using wrapper and filter approaches ranked first and third in performance among all relevant methods.
Journal ArticleDOI

Local Coordinate Concept Factorization for Image Representation

TL;DR: A locality constraint is introduced into the traditional CF by requiring the concepts (basis vectors) to be as close to the original data points as possible, each datum can be represented by a linear combination of only a few basis concepts.
Proceedings ArticleDOI

Network-wide Crowd Flow Prediction of Sydney Trains via Customized Online Non-negative Matrix Factorization

TL;DR: Intensive experiments on a large-scale, real-world dataset containing transactional data demonstrate the superiority of the proposed three online non-negative matrix factorization (ONMF) models.
Proceedings ArticleDOI

Single-channel source separation using simplified-training complex matrix factorization

TL;DR: A new method of creating learned sets of bases used in the matrix factorization technique for single-channel source separation, which does not suffer the complication of choosing an optimal number of bases as in previous methods is presented.
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