Hybrid ISTA: Unfolding ISTA With Convergence Guarantees Using Free-Form Deep Neural Networks
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DOI: 10.1109/tpami.2022.3172214
Abstract: It is promising to solve linear inverse problems by unfolding iterative algorithms (e.g., iterative shrinkage thresholding algorithm (ISTA)) as deep neural networks (DNNs) with learnable parameters. However, existing ISTA-based unfolded algorithms restrict the network architectures… read more here.
Keywords: hybrid ista; free form; deep neural; convergence ... See more keywords