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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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Journal ArticleDOI

Effect of power output on muscle coordination during rowing

TL;DR: The present study found that despite significant changes in the level of muscle activity, the global temporal and spatial organization of the motor output is very little affected by power output on a rowing ergometer.
Proceedings ArticleDOI

Distributional Inclusion Vector Embedding for Unsupervised Hypernymy Detection

TL;DR: Distributional inclusion vector embedding (DIVE) is introduced, a simple-to-implement unsupervised method of hypernym discovery via per-word non-negative vector embeddings which preserve the inclusion property of word contexts.
Proceedings Article

A linear ensemble of individual and blended models for music rating prediction

TL;DR: The four stages: individual model building, non-linear blending, linear ensemble and post-processing lead to a successful final solution, within which techniques on feature engineering and aggregation (blending and ensemble learning) play crucial roles.

Nonnegative matrix factorization with -divergence

TL;DR: A multiplicative updating algorithm which it is shown can be also derived using Karush-Kuhn-Tucker conditions as well as the projected gradient and the monotonic convergence of the algorithm is analyzed and proved.
Journal ArticleDOI

Local discriminative based sparse subspace learning for feature selection

TL;DR: A new unsupervised feature selection algorithm called local discriminative based sparse subspace learning for feature selection (LDSSL) is proposed, which can improve the discriminate ability of the algorithm, but also utilize the local geometric structure information contained in data.
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