Jinshi Yu

Orcid: 0000-0001-7930-5146

According to our database1, Jinshi Yu authored at least 15 papers between 2017 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
Low-rank sparse fully-connected tensor network for tensor completion.
Pattern Recognit., 2025

2023
Robust to Rank Selection: Low-Rank Sparse Tensor-Ring Completion.
IEEE Trans. Neural Networks Learn. Syst., May, 2023

Low tensor-ring rank completion: parallel matrix factorization with smoothness on latent space.
Neural Comput. Appl., March, 2023

Incomplete Multiview Clustering via Low-Rank Tensor Ring Completion.
Int. J. Intell. Syst., 2023

2022
Multi-Aspect Streaming Tensor Ring Completion for Dynamic Incremental Data.
IEEE Signal Process. Lett., 2022

Online subspace learning and imputation by Tensor-Ring decomposition.
Neural Networks, 2022

2021
Low Tensor-Ring Rank Completion by Parallel Matrix Factorization.
IEEE Trans. Neural Networks Learn. Syst., 2021

2020
An Efficient Tensor Completion Method Via New Latent Nuclear Norm.
IEEE Access, 2020

2019
An Efficient Tensor Completion Method via New Latent Nuclear Norm.
CoRR, 2019

Tensor-Ring Nuclear Norm Minimization and Application for Visual Data Completion.
CoRR, 2019

Tensor-ring Nuclear Norm Minimization and Application for Visual : Data Completion.
Proceedings of the IEEE International Conference on Acoustics, 2019

Low-rank Embedding of Kernels in Convolutional Neural Networks under Random Shuffling.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
Learning the Hierarchical Parts of Objects by Deep Non-Smooth Nonnegative Matrix Factorization.
IEEE Access, 2018

An Effective Tensor Completion Method Based on Multi-linear Tensor Ring Decomposition.
Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2018

2017
A new canonical polyadic decomposition algorithm with improved stability and its applications to biomedical signal processing.
Clust. Comput., 2017


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