A Continuous Restricted Boltzmann Machine with a Hardware-Amenable Learning Algorithm
نویسندگان
چکیده
This paper proposes a continuous stochastic generative model that offers an improved ability to model analogue data, with a simple and reliable learning algorithm. The architecture forms a continuous restricted Boltzmann Machine, with a novel learning algorithm. The capabilities of the model are demonstrated with both artificial and real data.
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تاریخ انتشار 2002