English

MCRM: Mother Compact Recurrent Memory

Neural and Evolutionary Computing 2019-08-08 v3 Machine Learning Machine Learning

Abstract

LSTMs and GRUs are the most common recurrent neural network architectures used to solve temporal sequence problems. The two architectures have differing data flows dealing with a common component called the cell state (also referred to as the memory). We attempt to enhance the memory by presenting a modification that we call the Mother Compact Recurrent Memory (MCRM). MCRMs are a type of a nested LSTM-GRU architecture where the cell state is the GRU hidden state. The concatenation of the forget gate and input gate interactions from the LSTM are considered an input to the GRU cell. Because MCRMs has this type of nesting, MCRMs have a compact memory pattern consisting of neurons that acts explicitly in both long-term and short-term fashions. For some specific tasks, empirical results show that MCRMs outperform previously used architectures.

Keywords

Cite

@article{arxiv.1808.02016,
  title  = {MCRM: Mother Compact Recurrent Memory},
  author = {Abduallah A. Mohamed and Christian Claudel},
  journal= {arXiv preprint arXiv:1808.02016},
  year   = {2019}
}

Comments

Submitted to AAAI-19

R2 v1 2026-06-23T03:25:46.299Z