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Abstract:
We solve the dynamics of on-line Hebbian learning in
perceptrons exactly, for the regime where the size of the training
set scales linearly with the number of inputs. We consider both
noiseless and noisy teachers. Our calculation cannot be extended to
non-Hebbian rules, but the solution provides a nice benchmark to
test more general and advanced theories for solving the dynamics of
learning with restricted training sets.
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