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1
Cross-Situational Learning Towards Robot Grounding
In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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Cross-Situational Learning Towards Robot Grounding
In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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3
What does the Canary Say? Low-Dimensional GAN Applied to Birdsong
In: https://hal.inria.fr/hal-03244723 ; 2021 (2021)
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4
What does the Canary Say? Low-Dimensional GAN Applied to Birdsong
In: https://hal.inria.fr/hal-03244723 ; 2021 (2021)
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Which Hype for my New Task? Hints and Random Search for Reservoir Computing Hyperparameters
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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6
Canary Song Decoder: Transduction and Implicit Segmentation with ESNs and LTSMs
In: https://hal.inria.fr/hal-03203374 ; 2021 (2021)
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Which Hype for my New Task? Hints and Random Search for Reservoir Computing Hyperparameters
In: https://hal.inria.fr/hal-03203318 ; 2021 (2021)
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.
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
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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8
Canary Song Decoder: Transduction and Implicit Segmentation with ESNs and LTSMs
In: ICANN 2021 - 30th International Conference on Artificial Neural Networks ; https://hal.inria.fr/hal-03203374 ; ICANN 2021 - 30th International Conference on Artificial Neural Networks, Sep 2021, Bratislava, Slovakia. pp.71--82, ⟨10.1007/978-3-030-86383-8_6⟩ ; https://link.springer.com/chapter/10.1007/978-3-030-86383-8_6 (2021)
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9
Hierarchical-Task Reservoir for Online Semantic Analysis from Continuous Speech
In: ISSN: 2162-237X ; IEEE Transactions on Neural Networks and Learning Systems ; https://hal.inria.fr/hal-03031413 ; IEEE Transactions on Neural Networks and Learning Systems, IEEE, 2021, ⟨10.1109/TNNLS.2021.3095140⟩ ; https://ieeexplore.ieee.org/abstract/document/9548713/metrics#metrics (2021)
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10
Editorial: Language and Robotics
In: ISSN: 2296-9144 ; Frontiers in Robotics and AI ; https://hal.inria.fr/hal-03533733 ; Frontiers in Robotics and AI, Frontiers Media S.A., 2021, 8, ⟨10.3389/frobt.2021.674832⟩ (2021)
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11
Learning to Parse Sentences with Cross-Situational Learning using Different Word Embeddings Towards Robot Grounding ...
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12
Cross-Situational Learning with Reservoir Computing for Language Acquisition Modelling
In: 2020 International Joint Conference on Neural Networks (IJCNN 2020) ; https://hal.inria.fr/hal-02594725 ; 2020 International Joint Conference on Neural Networks (IJCNN 2020), Jul 2020, Glasgow, Scotland, United Kingdom ; https://wcci2020.org/ (2020)
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13
Hierarchical-Task Reservoir for Anytime POS Tagging from Continuous Speech
In: 2020 International Joint Conference on Neural Networks (IJCNN 2020) ; https://hal.inria.fr/hal-02594495 ; 2020 International Joint Conference on Neural Networks (IJCNN 2020), Jul 2020, Glasgow, Scotland, United Kingdom ; https://wcci2020.org/ (2020)
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14
Language Acquisition with Echo State Networks: Towards Unsupervised Learning
In: ICDL 2020 - IEEE International Conference on Development and Learning ; https://hal.inria.fr/hal-02926613 ; ICDL 2020 - IEEE International Conference on Development and Learning, Oct 2020, Valparaiso / Virtual, Chile (2020)
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15
A Journey in ESN and LSTM Visualisations on a Language Task
In: https://hal.inria.fr/hal-03030248 ; 2020 (2020)
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16
Recurrent Neural Networks Models for Developmental Language Acquisition: Reservoirs Outperform LSTMs
In: SNL 2020 - 12th Annual Meeting of the Society for the Neurobiology of Language ; https://hal.inria.fr/hal-03146558 ; SNL 2020 - 12th Annual Meeting of the Society for the Neurobiology of Language, Oct 2020, Virtual Edition, Canada (2020)
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17
Learning to Parse Grounded Language using Reservoir Computing
In: ICDL-Epirob 2019 - Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics ; https://hal.inria.fr/hal-02422157 ; ICDL-Epirob 2019 - Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics, Aug 2019, Olso, Norway. ⟨10.1109/devlrn.2019.8850718⟩ ; https://ieeexplore.ieee.org/abstract/document/8850718 (2019)
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18
Teach Your Robot Your Language! Trainable Neural Parser for Modelling Human Sentence Processing: Examples for 15 Languages
In: ISSN: 2379-8920 ; EISSN: 2379-8939 ; IEEE Transactions on Cognitive and Developmental Systems ; https://hal.inria.fr/hal-01964541 ; IEEE Transactions on Cognitive and Developmental Systems, Institute of Electrical and Electronics Engineers, Inc, 2019, ⟨10.1109/TCDS.2019.2957006⟩ ; https://doi.org/10.1109/tcds.2019.2957006 (2019)
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19
A Reservoir Model for Intra-Sentential Code-Switching Comprehension in French and English
In: CogSci'19 - 41st Annual Meeting of the Cognitive Science Society ; https://hal.inria.fr/hal-02432831 ; CogSci'19 - 41st Annual Meeting of the Cognitive Science Society, Jul 2019, Montréal, Canada ; https://cognitivesciencesociety.org/cogsci-2019/ (2019)
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20
Replication of Laje & Mindlin's model producing synthetic syllables
In: European Birdsong Meeting ; https://hal.inria.fr/hal-01964522 ; European Birdsong Meeting, Apr 2018, Odense, Denmark. 2018 (2018)
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