会发现 Weight Decay 后的缩放系数其实对 BN 的输出没什么影响,那么其带来的正则也就没有什么用了。因为每次 Weight Decay 后,BN 又给整回来了。 那是不是有 BN 的情况下 Weight Decay 就可以不要了呢? 分析发现其实也不是的,反...
L2 Regularization and Batch Normblog.janestreet.com/l2-regularization-and-batch-norm/ 上来先是一个结论,l2 weight decay(wd)配合batch norm的效果就是对learning rate动态的调节! In particular, when used together with batch normalization in a convolutional neural net with typical architectures, an L2...
内容提示: F IX N ORM : D ISSECTING W EIGHT D ECAY FOR T RAIN -ING D EEP N EURAL N ETWORKSYucong Zhou, Yunxiao Sun & Zhao ZhongHuawei{zhouyucong1, sunyunxiao3, zorro.zhongzhao}@huawei.comA BSTRACTWeight decay is a widely used technique for training Deep Neural Net-works(DNN)....
代码中总是出现这样一句:no_decay = ["bias", "LayerNorm.bias", "LayerNorm.weight"] 将模型代码分为两类,参数中出现no_decay中的参数不进行优化,不太明白原因,今天终于找到了出处。但还没明白原因,According to AAAMLP book by A. Thakur, we generally do not use any decay for bias and LayerNorm....
Gate visuals: gates in gated architectures (LSTM, GRU) shown explicitly Channel visuals: cell units (feature extractors) shown explicitly General visuals: methods also applicable to CNNs & others Weight norm tracking: useful for analyzing weight decay ...
百度试题 题目机器学习中,下面哪个方法不是为了防止过拟合的? A. Batchnorm B. Dropout C. Weight decay D. Dropconnect E. Early stopping F. Data augmentation 相关知识点: 试题来源: 解析 A.Batchnorm 反馈 收藏