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Kernel based low-rank sparse model for single image super-resolution
Under the assumption that the sparse coeffcients for the nonlocal data in the kernel space should be low-rank, we impose low-rank constraint on sparse coding to share similarities among representation coeffcients and remove outliers in order that stable weights for SR reconstruction can be obtained.
Partial Off-Policy Learning: Balance Accuracy and Diversity for Human-Oriented Image Captioning
Human-oriented image captioning with both high diversity and accuracy is a challenging task in vision+language modeling.
Self-supervised On-device Federated Learning from Unlabeled Streams
The ubiquity of edge devices has led to a growing amount of unlabeled data produced at the edge.
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