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Which Hype for my New Task? Hints and Random Search for Reservoir Computing Hyperparameters
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In: ICANN 2021 - 30th International Conference on Artificial Neural Networks ; https://hal.inria.fr/hal-03203318 ; ICANN 2021 - 30th International Conference on Artificial Neural Networks, Sep 2021, Bratislava, Slovakia (2021)
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| 2 |
Which Hype for my New Task? Hints and Random Search for Reservoir Computing Hyperparameters
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In: https://hal.inria.fr/hal-03203318 ; 2021 (2021)
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Abstract:
In learning systems, hyperparameters are parameters that are not learned but need to be set a priori. In Reservoir Computing, there are several parameters that needs to be set a priori depending on the task. Newcomers to Reservoir Computing cannot have a good intuition on which hyperparameters to tune and how to tune them. For instance, beginners often explore the reservoir sparsity, but in practice this parameter is not of high influence on performance. Most importantly, many authors keep doing suboptimal hyperparameter searches: using grid search as a tool to explore more than two hyperparameters, while restraining the spectral radius to be below unity. In this short paper, we give some suggestions, intuitions, and give a general method to find robust hyperparameters while understanding their influence on performance. We also provide a graphical interface (included in ReservoirPy ) in order to make this hyperparameter search more intuitive. Finally, we discuss some potential refinements of the proposed method.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]; [SCCO.LING]Cognitive science/Linguistics; [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]; Echo State Networks; Effective Spectral Radius; Grid Search; Hyperparameters; Random Search; Reservoir Computing
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URL: https://hal.inria.fr/hal-03203318
https://hal.inria.fr/hal-03203318/document
https://hal.inria.fr/hal-03203318/file/Hinaut2021_ICANN_Reservoir-Random-Search_HAL-preprint-v1.pdf
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| 5 |
Adaptation au locuteur pour la séparation de la parole par NMF
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In: https://hal.sorbonne-universite.fr/hal-01482183 ; [Stage] STMS - Sciences et Technologies de la Musique et du Son UMR 9912 IRCAM-CNRS-UPMC. 2016 (2016)
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| 6 |
On the Generalization of Shannon Entropy for Speech Recognition
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In: IEEE workshop on Spoken Language Technology ; https://hal.sorbonne-universite.fr/hal-00737653 ; IEEE workshop on Spoken Language Technology, Dec 2012, United States (2012)
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| 7 |
Research on Narrowband Communications.
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In: DTIC AND NTIS (1982)
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| 8 |
Research on Narrowband Communications
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In: DTIC AND NTIS (1981)
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| 9 |
Research on Narrowband Communications
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In: DTIC AND NTIS (1981)
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| 11 |
Tutor Dialogue Planning with Contextual Information and Discourse Structure
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In: http://www.cs.cmu.edu/afs/cs/user/rwfisher/www/Curriculum_Vitae_files/fisher_simmons_its14.pdf
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