Reservoir Computing Trends
Zusammenfassung
Reservoir Computing (RC) is a paradigm of understanding and training Recurrent Neural Networks (RNNs) based on treating the recurrent part (the reservoir) differently than the readouts from it. It started ten years ago and is currently a prolific research area, giving important insights into RNNs, practical machine learning tools, as well as enabling computation with non-conventional hardware. Here we give a brief introduction into basic concepts, methods, insights, current developments, and highlight some applications of RC.
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- BibTeX
Lukoševičius, M., Jaeger, H. & Schrauwen, B.,
(2012).
Reservoir Computing Trends.
KI - Künstliche Intelligenz: Vol. 26, No. 4.
Springer.
(S. 365-371).
DOI: 10.1007/s13218-012-0204-5
@article{mci/Lukoševičius2012,
author = {Lukoševičius, Mantas AND Jaeger, Herbert AND Schrauwen, Benjamin},
title = {Reservoir Computing Trends},
journal = {KI - Künstliche Intelligenz},
volume = {26},
number = {4},
year = {2012},
,
pages = { 365-371 } ,
doi = { 10.1007/s13218-012-0204-5 }
}
author = {Lukoševičius, Mantas AND Jaeger, Herbert AND Schrauwen, Benjamin},
title = {Reservoir Computing Trends},
journal = {KI - Künstliche Intelligenz},
volume = {26},
number = {4},
year = {2012},
,
pages = { 365-371 } ,
doi = { 10.1007/s13218-012-0204-5 }
}
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Mehr Information
ISSN: 1610-1987
Datum: 2012
Typ: Text/Journal Article