Adaptive Learning Method of Recurrent Temporal Deep Belief Network to Analyze Time Series Data

11 Jul 2018 Takumi Ichimura Shin Kamada

Deep Learning has the hierarchical network architecture to represent the complicated features of input patterns. Such architecture is well known to represent higher learning capability compared with some conventional models if the best set of parameters in the optimal network structure is found... (read more)

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Methods used in the Paper


METHOD TYPE
Deep Belief Network
Generative Models
Restricted Boltzmann Machine
Generative Models