Abstract:In classification tasks, training labels are usually specified as one-hot targets which represent each class equally and exclusively. However, this labeling rule is not suitable in some situations. For the dependent classes, one-hot targets are not capable to represent the relation among them. The existing label smoothing methods just split the target response into neighboring classes, but it is only applied for ordinal classification, but not for the dependent but non-ordered classes. In this paper, we propos… Show more
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