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Jinshi Yu

2 accepted papers

2019

Low-rank Embedding of Kernels in Convolutional Neural Networks under Random Shuffling

ICASSP 2019accepted

Although the convolutional neural networks (CNNs) have become popular for various image processing and computer vision tasks recently, it remains a challenging problem to reduce the storage cost of the parameters for resource-limited platforms. In the previous studies, tensor decomposition (TD) has…

Cited by 0SourceScholar
2019

Tensor-ring Nuclear Norm Minimization and Application for Visual : Data Completion

ICASSP 2019accepted

Tensor ring (TR) decomposition has been successfully used to obtain the state-of-the-art performance in the visual data completion problem. However, the existing TR-based completion methods are severely non-convex and computationally demanding. In addition, the determination of the optimal TR rank i…

Cited by 0SourceScholar