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The batch update strategy allows the use of a fixed, but small, learning rate η t, which eliminates the problem of the weights getting stuck because the learning rate η t was decreased too quickly.
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As a result, training can fail simply because some hyperparameters, e.g., the learning rate, are slightly inappropriate.
Because in the RW model the learning rate reflects stimulus properties including salience (Rescorla and Wagner 1972), ϵTO can be assumed to be considerably smaller than ϵCS.
The learning rate annealing is an important aspect of co-adaptation because it controls to what extent the BMI adapts to the user.
ξ is the learning rate for Q-learning.
Specifically, we introduce the WoLF principle, "Win or Learn Fast", for varying the learning rate.
where and ∞ is the learning rate.
The learning rate is μ = 0.05.
Learning rate (LR) and momentum (M): We continue the analysis with the learning rate and momentum.
"In machine learning, this could be a small tweak in the learning rate of a model.
where δ is the learning rate used for the adaptation.
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