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Pruning and regularization in Reservoir Computing: a first insight

Xavier Dutoit, Benjamin Schrauwen (UGent) , Jan Van Campenhout (UGent) , Dirk Stroobandt (UGent) , Hendrik Van Brusssel and Marnix Nuttin
(2008) European Symposium on Artificial Neural Networks, 16th, Proceedings.
Author
Organization
Abstract
Reservoir Computing is a new paradigm for using Recurrent Neural Networks which shows promising results. However, as the recurrent part is created randomly, it typically needs to be large enough to be able to capture the dynamic features of the data considered. Moreover, this random creation is still lacking a strong methodology. We propose to study how pruning some connections from the reservoir to the readout can help on the one hand to increase the generalisation ability, in much the same way as regularisation techniques do, and on the other hand to improve the implementability of reservoirs in hardware. Furthermore we study the actual sub-reservoir which is kept after pruning which leads to important insights in what we have to expect from a good reservoir.
Keywords
pruning, reservoir computing, regularization

Citation

Please use this url to cite or link to this publication:

MLA
Dutoit, Xavier, et al. “Pruning and Regularization in Reservoir Computing: A First Insight.” European Symposium on Artificial Neural Networks, 16th, Proceedings, d-side publications, 2008.
APA
Dutoit, X., Schrauwen, B., Van Campenhout, J., Stroobandt, D., Van Brusssel, H., & Nuttin, M. (2008). Pruning and regularization in Reservoir Computing: a first insight. European Symposium on Artificial Neural Networks, 16th, Proceedings. Presented at the 16th European symposium on Artificial Neural Networks, Brugge, Belgium.
Chicago author-date
Dutoit, Xavier, Benjamin Schrauwen, Jan Van Campenhout, Dirk Stroobandt, Hendrik Van Brusssel, and Marnix Nuttin. 2008. “Pruning and Regularization in Reservoir Computing: A First Insight.” In European Symposium on Artificial Neural Networks, 16th, Proceedings. d-side publications.
Chicago author-date (all authors)
Dutoit, Xavier, Benjamin Schrauwen, Jan Van Campenhout, Dirk Stroobandt, Hendrik Van Brusssel, and Marnix Nuttin. 2008. “Pruning and Regularization in Reservoir Computing: A First Insight.” In European Symposium on Artificial Neural Networks, 16th, Proceedings. d-side publications.
Vancouver
1.
Dutoit X, Schrauwen B, Van Campenhout J, Stroobandt D, Van Brusssel H, Nuttin M. Pruning and regularization in Reservoir Computing: a first insight. In: European Symposium on Artificial Neural Networks, 16th, Proceedings. d-side publications; 2008.
IEEE
[1]
X. Dutoit, B. Schrauwen, J. Van Campenhout, D. Stroobandt, H. Van Brusssel, and M. Nuttin, “Pruning and regularization in Reservoir Computing: a first insight,” in European Symposium on Artificial Neural Networks, 16th, Proceedings, Brugge, Belgium, 2008.
@inproceedings{680771,
  abstract     = {{Reservoir Computing is a new paradigm for using Recurrent Neural Networks which shows promising results. However, as the recurrent part is created randomly, it typically needs to be large enough to be able to capture the dynamic features of the data considered. Moreover, this random creation is still lacking a strong methodology. We propose to study how pruning some connections from the reservoir to the readout can help on the one hand to increase the generalisation ability, in much the same way as regularisation techniques do, and on the other hand to improve the implementability of reservoirs in hardware. Furthermore we study the actual sub-reservoir which is kept after pruning which leads to important insights in what we have to expect from a good reservoir.}},
  author       = {{Dutoit, Xavier and Schrauwen, Benjamin and Van Campenhout, Jan and Stroobandt, Dirk and Van Brusssel, Hendrik and Nuttin, Marnix}},
  booktitle    = {{European Symposium on Artificial Neural Networks, 16th, Proceedings}},
  keywords     = {{pruning,reservoir computing,regularization}},
  language     = {{eng}},
  location     = {{Brugge, Belgium}},
  pages        = {{6}},
  publisher    = {{d-side publications}},
  title        = {{Pruning and regularization in Reservoir Computing: a first insight}},
  year         = {{2008}},
}