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hi~I have a question about the calculation of p_emp. As you mentioned in Appendix B, you use exponential moving average to calculate the p_emp. Why in the calculation of p_batch, you implement it by p_batch = torch.tensor([len(c) / len(train) for c in batch_by_class]) not p_batch = torch.tensor([len(c) / len(X_batch) for c in batch_by_class])?
Moreover, can you further explain the motivation of EMA, i.e. when the exact value of empirical label distribution is not available?
The text was updated successfully, but these errors were encountered:
hi~I have a question about the calculation of p_emp. As you mentioned in Appendix B, you use exponential moving average to calculate the p_emp. Why in the calculation of p_batch, you implement it by
p_batch = torch.tensor([len(c) / len(train) for c in batch_by_class])
notp_batch = torch.tensor([len(c) / len(X_batch) for c in batch_by_class])
?Moreover, can you further explain the motivation of EMA, i.e. when the exact value of empirical label distribution is not available?
The text was updated successfully, but these errors were encountered: