Repeating smaller datasets speeds up training via sampling biases that enable appropriate layer-wise growth, leading to compute savings over larger datasets across tasks and architectures.
2009 50th Annual IEEE Symposium on Foundations of Computer Science , pages=
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Less Data, Faster Training: repeating smaller datasets speeds up learning via sampling biases
Repeating smaller datasets speeds up training via sampling biases that enable appropriate layer-wise growth, leading to compute savings over larger datasets across tasks and architectures.