Recurrent Memory Array Structures

نویسنده

  • Kamil Rocki
چکیده

The following report introduces ideas augmenting standard Long Short Term Memory (LSTM) architecture with multiple memory cells per hidden unit in order to improve its generalization capabilities. It considers both deterministic and stochastic variants of memory operation. It is shown that the nondeterministic Array-LSTM approach improves stateof-the-art performance on character level text prediction achieving 1.402 BPC† on enwik8 dataset. Furthermore, this report estabilishes baseline neural-based results of 1.12 BPC and 1.19 BPC for enwik9 and enwik10 datasets respectively.

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عنوان ژورنال:
  • CoRR

دوره abs/1607.03085  شماره 

صفحات  -

تاریخ انتشار 2016