Backpropagation for a Linear Layer
During the backward pass through the linear layer, we assume that the derivative @L @Y has already been computed. For example if the linear layer is part of a linear classi er, then the matrix Y gives class scores; these scores are fed to a loss function (such as the softmax or multiclass SVM loss) which computes the scalar loss L and derivative @L
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