All Questions
Tagged with ce or cross-entropy
5 questions
10
votes
2
answers
12k
views
How do I handle negative rewards in policy gradients with the cross-entropy loss function?
I am using policy gradients in my reinforcement learning algorithm, and occasionally my environment provides a severe penalty (i.e. negative reward) when a wrong move is made. I'm using a neural ...
- 209
8
votes
1
answer
1k
views
Which loss function should I use in REINFORCE, and what are the labels?
I understand that this is the update for the parameters of a policy in REINFORCE:
$$
\Delta \theta_{t}=\alpha \nabla_{\theta} \log \pi_{\theta}\left(a_{t} \mid s_{t}\right) v_{t},
$$
where $v_t$ is ...
- 590
5
votes
3
answers
6k
views
In logistic regression, why is the binary cross-entropy loss function convex?
I am studying logistic regression for binary classification.
The loss function used is cross-entropy. For a given input $x$, if our model outputs $\hat{y}$ instead of $y$, the loss is given by
$$\text{...
- 3,990
2
votes
1
answer
2k
views
How does the implementation of the VAE's objective function equate to ELBO?
For a lot of VAE implementations I've seen in code, it's not really obvious to me how it equates to ELBO.
$$L(X)=H(Q)-H(Q:P(X,Z))=\sum_ZQ(Z)logP(Z,X)-\sum_ZQ(Z)log(Q(Z))$$
The above is the definition ...
- 805
-1
votes
1
answer
245
views
Why is the cross-entropy a cost function?
The question looks foolish, but I think cross-entropy is somewhat weird as a cost function.
As a cost function for linear regression, the mean square error $ \sum_{i=1}^{n} (y_i - (ax_i+b)) ^2$ seems ...
- 125