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 sigmoid
Search options not deleted
user 33354
For questions about the sigmoid functions (in particular, the logistic functions) and the consequences of using them as activation functions in neural networks.
4
votes
1
answer
960
views
Neural network doesn't seem to converge with ReLU but it does with Sigmoid?
I have been programming a multilayer perceptron in c++, and it seems to be working with a sigmoid function, however when I change the activation function to ReLU it does not converge and stays at an average … With the sigmoid function it converges rather nicely, I did a bit of testing and after about 1000 generations it got to an average cost of 0.1 on the first 1000 items in the MNIST dataset. …
- 151