Multiexpert Adversarial Regularization for Robust and Data-Efficient Deep Supervised Learning
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DOI: 10.1109/access.2022.3196780
Abstract: Deep neural networks (DNNs) can achieve high accuracy when there is abundant training data that has the same distribution as the test data. In practical applications, data deficiency is often a concern. For classification tasks,… read more here.
Keywords: supervised learning; robust data; data efficient; deep supervised ... See more keywords