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Abstract: Learning to store information over extended time intervals via recurrent backpropagation takes a very long time, mostly due to insufficient, decaying error back flow. We briefly review Hochreiter's 1991 analysis of this problem, then address it by introducing a novel, efficient method called "Long Short-Term Memory" (LSTM). LSTM can learn to bridge time lags in excess of 1000 steps by enforcing constant error flow through "constant error carrousels" within special units. Multiplicative gate... (Update)
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BibTeX entry: (Update)
Hochreiter, S., & Schmidhuber, J. (1997). Long short-term memory. Neural Computation, 9(8), 1735--1780. http://citeseer.ist.psu.edu/hochreiter96long.html More
@article{ hochreiter97long,
author = "Sepp Hochreiter and Jurgen Schmidhuber",
title = "Long Short-Term Memory",
journal = "Neural Computation",
volume = "9",
number = "8",
pages = "1735-1780",
year = "1997",
url = "citeseer.ist.psu.edu/hochreiter96long.html" }
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