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Abstract: Recurrent neural networks that are trained to behave like deterministic finite-state automata (DFAs) can show deteriorating performance when tested on long strings. This deteriorating performance can be attributed to the instability of the internal representation of the learned DFA states. The use of a sigmoidal discriminant function together with the recurrent structure contribute to this instability. We prove that a simple algorithm can construct second-order recurrent neural networks with a... (Update)
Context of citations to this paper: More
.... feeds back into the input) have been constructed to map single sequences of equal length from an input language to an output language [48, 103]. This idea of encoding finitestate automata into an RNN has recently been refined into what is called neural transducers [135] To...
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BibTeX entry: (Update)
Omlin, C. W., Giles, C. L.: Constructing deterministic finite-state automata in recurrent neural networks. Journal of the ACM, 43, 937--972, 1996. http://citeseer.ist.psu.edu/article/omlin96constructing.html More
@inproceedings{ omlin94constructing,
author = "C. W. Omlin and C. L. Giles",
title = "Constructing deterministic finite-state automata in sparse recurrent neural networks",
booktitle = "{IEEE} International Conference on Neural Networks ({ICNN}'94)",
publisher = "IEEE Press",
address = "Piscataway, NJ",
pages = "1732--1737",
year = "1994",
url = "citeseer.ist.psu.edu/article/omlin96constructing.html" }
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29 Using knowledge-based neural networks to improve algorithms:.. - Maclin, Shavlik - 1993
28 Representation of finite state automata in recurrent radial .. - Frasconi, Gori et al. - 1996
26 Inserting rules into recurrent neural networks (context) - Giles, Omlin - 1992
26 Training second-order recurrent neural networks using hints - Omlin, Giles - 1992
25 The dynamics of discrete-time computation, with application .. (context) - Casey - 1996
24 A unified approach for integrating explicit knowledge and le.. (context) - Frasconi, Gori et al. - 1991
24 Combining symbolic and neural learning (context) - Shavlik - 1994
21 Rule revision with recurrent neural networks - Omlin, Giles - 1996
18 Second-order recurrent neural networks for grammatical infer.. (context) - Giles, Chen et al. - 1991
16 Recurrent neural networks and prior knowledge for sequence p.. - Frasconi, Gori et al. - 1995
15 Stable encoding of large finite-state automata in recurrent .. - Omlin, Giles - 1996
13 Dynamic recurrent neural networks: Theory and applications (context) - Giles, Kuhn et al. - 1994
11 Rule refinement with recurrent neural networks (context) - Giles, Omlin - 1993
9 Saturation at high gain in discrete time recurrent networks (context) - Hirsch - 1994
5 formation Processing and VLSI. Boston, MA: Kluwer Academic P.. (context) - Sheu, In - 1995
3 Personal Communication (context) - Horne
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