Abstract: We propose an sparse Bayesian learning (SBL)based method that leverages group sparsity and multiple parameterized dictionaries to detect the relevant dictionary entries and estimate their ...
Abstract: Self-supervised learning (SSL) has emerged as a promising approach for pretraining tasks by learning latent task-agnostic representations without labels. Currently, the pretrained SSL models ...
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