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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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Sample Complexity of Dictionary Learning and other Matrix Factorizations

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Sparse non-negative tensor factorization using columnwise coordinate descent

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A unifying model of concurrent spatial and temporal modularity in muscle activity

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Daily-Aware Personalized Recommendation based on Feature-Level Time Series Analysis

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Past review, current progress, and challenges ahead on the cocktail party problem

TL;DR: This overview paper focuses on the speech separation problem given its central role in the cocktail party environment, and describes the conventional single-channel techniques such as computational auditory scene analysis (CASA), non-negative matrix factorization (NMF) and generative models, and the newly developed deep learning-based techniques.
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