60 citations · 64 across the 8 of their papers we have counts for
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cs.LG2020
A One-step Approach to Covariate Shift Adaptation
Tianyi Zhang, Ikko Yamane, Nan Lu +1
A default assumption in many machine learning scenarios is that the training and test samples are drawn from the same probability distribution. However, such an assumption is often…
cs.LG2020★ 60 cited
Do We Need Zero Training Loss After Achieving Zero Training Error?
Takashi Ishida, Ikko Yamane, Tomoya Sakai +2
Overparameterized deep networks have the capacity to memorize training data with zero \emph{training error}. Even after memorization, the \emph{training loss} continues to approach…