4 votes

Learning an identity function with convolutional networks

Learning the identity function is not trivial at all. The main reason is that the identity function is linear, and a neural network try to approximate it in a non linear fashion. Non linear ...
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2 votes
Accepted

Why and how can the policy and value iteration methods converge to the OPTIMAL point?

These two algorithms converge to the optimal value function because they are instances of the generalization policy iteration, so they iteratively perform one policy evaluation (PE) step followed by ...
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  • 34.5k
1 vote
Accepted

Is it possible learning convergence is lost in Reinforcement Learning as the state space grows?

With tabular reinforcement learning (RL) methods, then catastrophic forgetting does not come into play, as it is a feature of online learning with approximators such as neural networks. Essentially ...
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  • 24.5k
1 vote

What can I infer if my model is converging extremely fast?

send us your loss function plot over epochs ( or steps ). this will help to get a better guidance(use log scale for loss axis). sending more details of your learning process may help too. but in this ...
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