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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

Efficient B-Mode Ultrasound Image Reconstruction From Sub-Sampled RF Data Using Deep Learning

TL;DR: In this article, a deep learning approach was proposed to interpolate the missing RF data by utilizing redundancy in the Rx-Xmit plane, which can effectively reduce the data rate without sacrificing the image quality.
Proceedings ArticleDOI

Temporal QoS-aware web service recommendation via non-negative tensor factorization

TL;DR: A Temporal QoS-aware Web Service Recommendation Framework is presented to predict missing QoS value under various temporal context and a Non-negative Tensor Factorization (NTF) algorithm is proposed which is able to deal with the triadic relations of user-service-time model.
Proceedings ArticleDOI

Deep neural networks for single channel source separation

TL;DR: The experimental results show that using DNN initialized by NMF for source separation improves the quality of the separated signal compared with using NMF with the same quality of signal.
Journal ArticleDOI

Texture and shape information fusion for facial expression and facial action unit recognition

TL;DR: A novel method based on fusion of texture and shape information is proposed for facial expression and Facial Action Unit (FAU) recognition from video sequences and the accuracy achieved is 92.3% when recognizing the seven basic facial expressions.
Journal ArticleDOI

Orthogonal matrix factorization enables integrative analysis of multiple RNA binding proteins.

TL;DR: An integrative orthogonality-regularized nonnegative matrix factorization (iONMF) is developed to integrate multiple data sources and discover non-overlapping, class-specific RNA binding patterns of varying strengths, and it is shown that the integration ofmultiple data sources improves the predictive accuracy of retrieval of RNA binding sites.
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