Recurrent Orthogonal Networks and Long-Memory Tasks

Abstract

Although RNNs have been shown to be powerful tools for processing sequential data, finding architectures or optimization strategies that allow them to model very long term dependencies is still an active area of research. In this work, we carefully analyze two synthetic datasets originally outlined in (Hochreiter & Schmidhuber, 1997) which are used to… (More)

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