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cond-mat.dis-nn2024
Fundamental operating regimes, hyper-parameter fine-tuning and glassiness: towards an interpretable replica-theory for trained restricted Boltzmann machines
Alberto Fachechi, Elena Agliari, Miriam Aquaro +2
We consider restricted Boltzmann machines with a binary visible layer and a Gaussian hidden layer trained by an unlabelled dataset composed of noisy realizations of a single ground…
cond-mat.dis-nn2024
Learning in Associative Networks through Pavlovian Dynamics
Daniele Lotito, Miriam Aquaro, Chiara Marullo
Hebbian learning theory is rooted in Pavlov's Classical Conditioning. While mathematical models of the former have been proposed and studied in the past decades, especially in spin…