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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.
$$
\mathbf {
\bbox[10px, border:2px solid red] { \color{red}{
\begin{aligned …
1
vote
Jacobian Matrix of an Element wise operation on a Matrix
Adding the answer as per the explanation by @whuber
$$
\begin{aligned}
\text{Let's take a 2x2 matrix , X } =
\begin{bmatrix}
x_{{1}{1}} & x_{{1}{2}} \\
x_{{2}{1}} & …
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 …
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). …
0
votes
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 …