Learning and Retrieval Operational Modes for Three-Layer Restricted Boltzmann Machines
نویسندگان
چکیده
We consider a three-layer restricted Boltzmann machine, where the two visible layers (encoding for input and output, respectively) are made of binary neurons while hidden layer is Gaussian neurons, we show formal equivalence with Hopfield model. The machine architecture allows different learning operational modes: when all free to evolve recover standard model whose size corresponds overall neurons; clamped model, output layer, endowed an external field as well additional slow noise. former stems from signal provided by tends favour retrieval, latter can be related statistical properties training set impair retrieval performance network. address this rigorous techniques, finding explicit expression its free-energy, whence phase-diagram showing system parameters tuned.
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ژورنال
عنوان ژورنال: Journal of Statistical Physics
سال: 2021
ISSN: ['0022-4715', '1572-9613']
DOI: https://doi.org/10.1007/s10955-021-02841-y