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Graph regularized low-rank tensor representation for feature selection

Published:2018-10 Issue: Volume:56 Page:234-244
ISSN:1047-3203
Container-title:Journal of Visual Communication and Image Representation
language:en
Short-container-title:Journal of Visual Communication and Image Representation

Author:

Su Yuting^ORCID,Bai Xu,Li Wu,Jing Peiguang^ORCID,Zhang Jing,Liu Jing

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Media Technology,Signal Processing

Reference56 articles.

1. Multimedia answering: enriching text qa with media information;Nie,2011

2. Exploring auxiliary context: discrete semantic transfer hashing for scalable image retrieval;Zhu;IEEE Trans. Neural Networks Learn. Syst.,2018

3. Unifying virtual and physical worlds: learning toward local and global consistency;Wang;ACM Trans. Inform. Syst.,2017

4. On effective location-aware music recommendation;Cheng;ACM Trans. Inform. Syst.,2016

5. Transfer independently together: a generalized framework for domain adaptation;Li;IEEE Trans. Cybernet.,2018

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1. Low-rank and Smooth Tensor Recovery on Cartesian Product Graphs;2023 International Conference on Sampling Theory and Applications (SampTA);2023-07-10

2. Unsupervised Feature Selection via Graph Regularized Nonnegative CP Decomposition;IEEE Transactions on Pattern Analysis and Machine Intelligence;2023-02-01

3. Robust estimation of highly corrupted low‐rank matrix via alternating direction method of multiplier;IET Signal Processing;2022-10-27

4. Gaussian noise robust face hallucination via average filtering based data fidelity and locality regularization;Applied Intelligence;2022-07-27

5. GLOSS: Tensor-based anomaly detection in spatiotemporal urban traffic data;Signal Processing;2022-03

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