Reservoir memory machines

Paaßen B, Schulz A (2020)
In: Proceedings of the 28th European Symposium on Artificial Neural Networks (ESANN 2020). Verleysen M (Ed); Bruges: i6doc: 567-572.

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Herausgeber*in
Verleysen, Michel
Abstract / Bemerkung
In recent years, Neural Turing Machines have gathered attention by joining the flexibility of neural networks with the computational capabilities of Turing machines. However, Neural Turing Machines are notoriously hard to train, which limits their applicability. We propose reservoir memory machines, which are still able to solve some of the benchmark tests for Neural Turing Machines, but are much faster to train, requiring only an alignment algorithm and linear regression. Our model can also be seen as an extension of echo state networks with an external memory, enabling arbitrarily long storage without interference.
Stichworte
echo state networks; reservoir computing; neural turing machines; memory-augmented neural networks
Erscheinungsjahr
2020
Titel des Konferenzbandes
Proceedings of the 28th European Symposium on Artificial Neural Networks (ESANN 2020)
Seite(n)
567-572
Konferenz
28th European Symposium on Artificial Neural Networks (ESANN 2020)
Konferenzort
Bruges
Konferenzdatum
2020-04-22 – 2020-04-24
Page URI
https://pub.uni-bielefeld.de/record/2941931

Zitieren

Paaßen B, Schulz A. Reservoir memory machines. In: Verleysen M, ed. Proceedings of the 28th European Symposium on Artificial Neural Networks (ESANN 2020). Bruges: i6doc; 2020: 567-572.
Paaßen, B., & Schulz, A. (2020). Reservoir memory machines. In M. Verleysen (Ed.), Proceedings of the 28th European Symposium on Artificial Neural Networks (ESANN 2020) (pp. 567-572). Bruges: i6doc.
Paaßen, Benjamin, and Schulz, Alexander. 2020. “Reservoir memory machines”. In Proceedings of the 28th European Symposium on Artificial Neural Networks (ESANN 2020), ed. Michel Verleysen, 567-572. Bruges: i6doc.
Paaßen, B., and Schulz, A. (2020). “Reservoir memory machines” in Proceedings of the 28th European Symposium on Artificial Neural Networks (ESANN 2020), Verleysen, M. ed. (Bruges: i6doc), 567-572.
Paaßen, B., & Schulz, A., 2020. Reservoir memory machines. In M. Verleysen, ed. Proceedings of the 28th European Symposium on Artificial Neural Networks (ESANN 2020). Bruges: i6doc, pp. 567-572.
B. Paaßen and A. Schulz, “Reservoir memory machines”, Proceedings of the 28th European Symposium on Artificial Neural Networks (ESANN 2020), M. Verleysen, ed., Bruges: i6doc, 2020, pp.567-572.
Paaßen, B., Schulz, A.: Reservoir memory machines. In: Verleysen, M. (ed.) Proceedings of the 28th European Symposium on Artificial Neural Networks (ESANN 2020). p. 567-572. i6doc, Bruges (2020).
Paaßen, Benjamin, and Schulz, Alexander. “Reservoir memory machines”. Proceedings of the 28th European Symposium on Artificial Neural Networks (ESANN 2020). Ed. Michel Verleysen. Bruges: i6doc, 2020. 567-572.

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arXiv: 2003.04793

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