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Computer Science > Emerging Technologies

Title: Reservoir Computing Benchmarks: a review, a taxonomy, some best practices

Abstract: Reservoir Computing is an Unconventional Computation model to perform computation on various different substrates, such as RNNs or physical materials. The method takes a "black-box" approach, training only the outputs of the system it is built on. As such, evaluating the computational capacity of these systems can be challenging. We review and critique the evaluation methods used in the field of Reservoir Computing. We introduce a categorisation of benchmark tasks. We review multiple examples of benchmarks from the literature as applied to reservoir computing, and note their strengths and shortcomings. We suggest ways in which benchmarks and their uses may be improved to the benefit of the reservoir computing community
Comments: 36pp, 15figs, review article
Subjects: Emerging Technologies (cs.ET); Machine Learning (cs.LG); Neural and Evolutionary Computing (cs.NE)
Cite as: arXiv:2405.06561 [cs.ET]
  (or arXiv:2405.06561v1 [cs.ET] for this version)

Submission history

From: Susan Stepney [view email]
[v1] Fri, 10 May 2024 16:02:41 GMT (3178kb,D)

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