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A function used to quantify the difference between observed data and predicted values according to a model. Minimization of loss functions is a way to estimate the parameters of the model.
11
votes
1
answer
7k
views
Loss not decreasing but performance is improving
I am training a custom implementation of DQN on the SpaceInvaders environment from OpenAI gym. The episode reward keeps increasing and approximately reaches the maximum episode reward that DQN achieve …
3
votes
1
answer
855
views
Huber Loss on top of Cross Entropy
I know that the Huber loss is usually applied on top of the L2 loss in order to prevent exploding gradients. Does it make sense to use the Huber loss on top of the cross entropy loss, though? I have a …