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作者你好,最近才看到这篇关于长尾数据分类的论文。有一些地方不是很明白。 1)论文指出验证或测试时才需要消除头部偏移的影响,那么消除头部偏移影响后,模型在训练集上的表现如何? 2)该偏移可以看作零输入的特征输出,那么能否将网络中所有卷积和BatchNormalization的bias均设置为否? 3) alpha的含义是什么,为什么可以大于1
谢谢
The text was updated successfully, but these errors were encountered:
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作者你好,最近才看到这篇关于长尾数据分类的论文。有一些地方不是很明白。

1)论文指出验证或测试时才需要消除头部偏移的影响,那么消除头部偏移影响后,模型在训练集上的表现如何?
2)该偏移可以看作零输入的特征输出,那么能否将网络中所有卷积和BatchNormalization的bias均设置为否?
3) alpha的含义是什么,为什么可以大于1
谢谢
The text was updated successfully, but these errors were encountered: