SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning

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Other Links: arxiv.org

Abstract:

Deep learning with noisy labels is a challenging task. Recent prominent methods that build on a specific sample selection (SS) strategy and a specific semi-supervised learning (SSL) model achieved state-of-the-art performance. Intuitively, better performance could be achieved if stronger SS strategies and SSL models are employed. Follow...More

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