Hi,
I am wondering where is dropout exactly added. For fc layers of y=Wx+b, dropout randomly drops the parameters of in W matrix rather than the feature x, and for conv layers, dropout randomly drops the parameters in the convolution kernels rather than the feature maps. Is this what exactly happens in the dropout layers?