Narrative survey highlights machine learning techniques for recovering corrupted data, indicating significant advancements.
This preprint presents a narrative survey and conceptual synthesis of machine learning approaches applied to corrupted data recovery, including supervised, unsupervised, generative, transformer-based, and reinforcement learning methods.
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Erika Conta (2026) studied this question.
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