Fundamental sampling patterns for low-rank multi-view data completion-Reference-Cited by-同舟云学术

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Fundamental sampling patterns for low-rank multi-view data completion

Published:2020-07 Issue: Volume:103 Page:107307
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Ashraphijuo Morteza,Wang Xiaodong,Aggarwal Vaneet^ORCID

Funder

Office of Naval Research

National Science Foundation

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference47 articles.

1. High-dimensional data analysis: the curses and blessings of dimensionality;Donoho,2000

2. Matrix completion problems: a survey;Johnson,1990

3. The power of convex relaxation: near-optimal matrix completion;Candès;IEEE Trans. Inform. Theory,2010

4. Sparse multiple kernel learning for signal processing applications;Subrahmanya;IEEE Trans. Pattern Anal. Mach.Intell.,2010

5. Low-rank multi-view learning in matrix completion for multi-label image classification;Liu,2015

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1. Mixed Matrix Completion in Complex Survey Sampling under Heterogeneous Missingness;Journal of Computational and Graphical Statistics;2024-03-29

2. Erratum: An Improved Low-Rank Matrix Fitting Method Based on Weighted L1,p Norm Minimization for Matrix Completion;International Journal of Pattern Recognition and Artificial Intelligence;2023-10

3. Fusion and Enhancement of Consensus Matrix for Multi-View Subspace Clustering;Mathematics;2023-03-20

4. An Improved Low-Rank Matrix Fitting Method Based on Weighted L1,p Norm Minimization for Matrix Completion;International Journal of Pattern Recognition and Artificial Intelligence;2023-03-15

5. Multi-Modal Brain Tumor Data Completion Based on Reconstruction Consistency Loss;Journal of Digital Imaging;2023-03-01

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