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勾配消失問題の疑似正規化法による緩和
Yun Bu1, Wenbo Jiang1, Gang Lu1
1School of Electrical Engineering and Electronic Information, Xihua University, Chengdu 610039, China.
Entropy (Basel, Switzerland)
|January 28, 2026
まとめ
疑似正規化は、勾配消失と勾配爆発を防ぐために勾配を拡大することにより、ディープラーニングのトレーニングを強化します。画像分類に適用されるこの新しいアプローチは、カテゴリ分類のために輪郭情報をユニークに利用します。
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