Bi-level Multi-objective Evolution of a Multi-layered Echo-State Network Autoencoder for Data Representations

    Neurocomputing, 2019.

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    Abstract:

    Abstract The Multi-Layered Echo-State Network (ML-ESN) is a recently developed, highly powerful type of recurrent neural network. It has succeeded in dealing with several non-linear benchmark problems. On account of its rich dynamics, ML-ESN is exploited in this paper, for the first time, as a recurrent Autoencoder (ML-ESNAE) to extract...More

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