Search Results
| Search type | Search syntax |
|---|---|
| Tags | [tag] |
| Exact | "words here" |
| Author |
user:1234 user:me (yours) |
| Score |
score:3 (3+) score:0 (none) |
| Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
| Views | views:250 |
| Code | code:"if (foo != bar)" |
| Sections |
title:apples body:"apples oranges" |
| URL | url:"*.example.com" |
| Saves | in:saves |
| Status |
closed:yes duplicate:no migrated:no wiki:no |
| Types |
is:question is:answer |
| Exclude |
-[tag] -apples |
| For more details on advanced search visit our help page | |
Results tagged with backpropagation
Search options not deleted
user 248568
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
CNN - upsampling backprop gradients across average-pooling layer
This is based on gunes's answer above.
We can vectorize all the matrices as follows:
$$
\mathrm{vec}(A^{[l]}) = \begin{bmatrix}
a_{11} \\
a_{21} \\
a_{31} \\
a_{12} \\
a_{22} \\
a_{32} \\
a_{13} \\
…
- 240
3
votes
2
answers
1k
views
CNN - upsampling backprop gradients across average-pooling layer
"Derivation of backpropagation in convolutional neural network (cnn)." University of Tennessee, Knoxville, TN (2016). …
- 240