Mini-batch Sampling Strategies for Long-Tailed Image Classification: An Empirical Study on CIFAR-100-LT
It is indicated that when rebalancing is applied during training matters as much as how much rebalancing is applied, which exposes the tension between unbiased optimisation of the empirical loss and fair representation of rare classes.
Si-Yu Yuan
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