Long short-term memory in recurrent neural networks
Infoscience (Ecole Polytechnique Fédérale de Lausanne)Published 1 January 2001Open access
Felix A. Gers
Citations235
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These Ecole polytechnique federale de Lausanne EPFL, n° 2366 (2001)Faculte informatique et communicationsJury: Paolo Frasconi, Roger Hersch, Martin Rajman, Jurgen Schmidhuber Public defense.
Abstract
These Ecole polytechnique federale de Lausanne EPFL, n° 2366 (2001)Faculte informatique et communicationsJury: Paolo Frasconi, Roger Hersch, Martin Rajman, Jurgen Schmidhuber Public defense: 2001-4-6 Reference doi:10.5075/epfl-thesis-2366Print copy in library catalog Record created on 2005-03-16, modified on 2016-08-08
Keywords
Computer SciencePhysics and Astronomy
Applied Physics Letters10.1162/153244303768966139
319 Citations2000
This work finds that LSTM augmented by "peephole connections" from its internal cells to its multiplicative gates can learn the fine distinction between sequences of spikes spaced either 50 or 49 time steps apart without the help of any short training exemplars.
Artificial Neural Nets and Genetic AlgorithmsLong Short-Term Memory Learns Context Free and Context Sensitive Languages
22 Citations2001Felix A. Gers, Jürgen Schmidhuber
LSTM variants are also the first RNNs to learn a context sensitive language (\mbox{CSL}), namely $a^nb^n c^n$.