2 citations · 3 across the 2 of their papers we have counts for
2 papers
stat.ML2020★ 2 cited
Consistent Batch Normalization for Weighted Loss in Imbalanced-Data Environment
Muneki Yasuda, Yeo Xian En, Seishirou Ueno
In this study, classification problems based on feedforward neural networks in a data-imbalanced environment are considered. Learning from an imbalanced dataset is one of the most…
stat.ML2019★ 1 cited
Improvement of Batch Normalization in Imbalanced Data
Muneki Yasuda, Seishirou Ueno
In this study, we consider classification problems based on neural networks in data-imbalanced environment. Learning from an imbalanced data set is one of the most important and pr…