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Imputing Out-of-Vocabulary Embeddings with LOVE Makes Language Models Robust with Little Cost
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In: ACL 2022 - 60th Annual Meeting of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-03613101 ; ACL 2022 - 60th Annual Meeting of the Association for Computational Linguistics, May 2022, Dublin, Ireland (2022)
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Imputing out-of-vocabulary embeddings with LOVE makes language models robust with little cost
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In: ACL 2022 - 60th Annual Meeting of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-03613101 ; ACL 2022 - 60th Annual Meeting of the Association for Computational Linguistics, May 2022, Dublin, Ireland (2022)
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Population modeling with machine learning can enhance measures of mental health
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In: ISSN: 2047-217X ; GigaScience ; https://hal.inria.fr/hal-03470466 ; GigaScience, BioMed Central, 2021, ⟨10.1101/2020.08.25.266536⟩ (2021)
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Population modeling with machine learning can enhance measures of mental health
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In: Gigascience (2021)
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Exploring the anatomical encoding of voice with a mathematical model of the vocal system.
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In: ISSN: 1053-8119 ; EISSN: 1095-9572 ; NeuroImage ; https://hal.inria.fr/hal-01498364 ; NeuroImage, Elsevier, 2016, 141, pp.31-9. ⟨10.1016/j.neuroimage.2016.07.033⟩ (2016)
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Identification of Mood-Relevant Brain Connections Using a Continuous, Subject-Driven Rumination Paradigm
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Identification of Mood-Relevant Brain Connections Using a Continuous, Subject-Driven Rumination Paradigm.
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In: ISSN: 1047-3211 ; EISSN: 1460-2199 ; Cerebral Cortex ; https://hal.inria.fr/hal-01094759 ; Cerebral Cortex, Oxford University Press (OUP), 2014, pp.12 (2014)
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API design for machine learning software: experiences from the scikit-learn project
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Buitinck, Lars; Louppe, Gilles; Blondel, Mathieu; Pedregosa, Fabian; Mueller, Andreas; Grisel, Olivier; Niculae, Vlad; Prettenhofer, Peter; Gramfort, Alexandre; Grobler, Jaques; Layton, Robert; Vanderplas, Jake; Joly, Arnaud; Holt, Brian; Varoquaux, Gaël
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In: European Conference on Machine Learning and Principles and Practices of Knowledge Discovery in Databases ; https://hal.inria.fr/hal-00856511 ; European Conference on Machine Learning and Principles and Practices of Knowledge Discovery in Databases, Sep 2013, Prague, Czech Republic (2013)
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Abstract:
International audience ; Scikit-learn is an increasingly popular machine learning li- brary. Written in Python, it is designed to be simple and efficient, accessible to non-experts, and reusable in various contexts. In this paper, we present and discuss our design choices for the application programming interface (API) of the project. In particular, we describe the simple and elegant interface shared by all learning and processing units in the library and then discuss its advantages in terms of composition and reusability. The paper also comments on implementation details specific to the Python ecosystem and analyzes obstacles faced by users and developers of the library.
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Keyword:
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; ACM: D.: Software/D.3: PROGRAMMING LANGUAGES; ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.5: Programming Languages and Software; ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.6: Learning; language design; Machine learning; Python; software engineering
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URL: https://hal.inria.fr/hal-00856511/file/paper.pdf
https://hal.inria.fr/hal-00856511/document
https://hal.inria.fr/hal-00856511
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| 9 |
Decoding Visual Percepts Induced by Word Reading with fMRI
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In: Pattern Recognition in NeuroImaging (PRNI), 2012 International Workshop on ; https://hal.inria.fr/hal-00730768 ; Pattern Recognition in NeuroImaging (PRNI), 2012 International Workshop on, Jul 2012, Londres, United Kingdom. pp.13-16, ⟨10.1109/PRNI.2012.20⟩ ; http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6295916&tag=1 (2012)
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