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Backpropagation, an abbreviation for "backward propagation of errors", is a common method of training artificial neural networks used in conjunction with an optimization method such as gradient descent.

2 votes

Backpropagation with Softmax / Cross Entropy

However writing this out for those who have come here for the general question of Backpropagation with Softmax and Cross-Entropy. $$ \mathbf { \bbox[10px, border:2px solid red] { \color{red}{ \begin{aligned …
Alex Punnen's user avatar
1 vote

Jacobian Matrix of an Element wise operation on a Matrix

Adding the answer as per the explanation by @whuber $$ \begin{aligned} \text{Let's take a 2x2 matrix , X } = \begin{bmatrix} x_{{1}{1}} & x_{{1}{2}} \\ x_{{2}{1}} & …
Alex Punnen's user avatar
0 votes
1 answer
1k views

Jacobian Matrix of an Element wise operation on a Matrix

Is it right in saying that the Jacobian Matrix of a Matrix output of an elementwise operation to the same input is a diagonal matrix ? Context below. From ref 1 it is clear that when you have an eleme …
Alex Punnen's user avatar
0 votes
1 answer
206 views

Back Propagation Derivation - where am I going wrong

The main thing is that I tried to derive out backpropagation via chain rule etc. … I tried to implement a simple CNN to test this out; however, during backpropagation, the weights are not matching. Even when I try to do Hadamard product (element-wise multiplication). …
Alex Punnen's user avatar
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Accepted

Back Propagation Derivation - where am I going wrong

The equations were correct. I had done a mistake in the code ; there were some element wise operations and some dot product type operations. It is corrected now - code print("-----------Back Propog …
Alex Punnen's user avatar