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Proceedings Article
Realtime Multiple Pitch Observation using Sparse Non-negative Constraints
TL;DR: A new approach for realtime multiple pitch observation of musical instruments and the decomposition algorithm consists of an algorithm for efficient decomposition of a spectrum using known pitch structures and based on sparse non-negative constraints.
Proceedings ArticleDOI
Accurate recovery of Internet traffic data: A tensor completion approach
TL;DR: This paper is the first to apply the tensor to model Internet traffic data to well exploit their hidden structures and propose a sequential tensor completion algorithm to significantly speed up the traffic data recovery process.
Posted Content
Effective Spectral Unmixing via Robust Representation and Learning-based Sparsity
TL;DR: A novel model is proposed by emphasizing both robust representation and learning-based sparsity, preventing outlier channels from dominating the authors' objective and achieving very accurate guidance maps and much better HU results compared with state-of-the-art methods.
Journal ArticleDOI
DeepFakE: improving fake news detection using tensor decomposition-based deep neural network
TL;DR: The proposed model (DeepFakE) outperforms with the existing fake news detection methods by applying deep learning on combined news content and social context-based features as an echo-chamber.
Journal ArticleDOI
Discriminative Nonnegative Spectral Clustering with Out-of-Sample Extension
TL;DR: A novel clustering algorithm to explicitly impose an additional nonnegative constraint on the cluster indicator matrix to seek for a more interpretable solution is proposed and an effective regularization term is shown which is able to not only provide more useful discriminative information but also learn a mapping function to predict cluster labels for the out-of-sample test data.
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