Výsledky vyhledávání - "Chedy Raïssi"

Akademický článek

Syntax-based transfer learning for the task of biomedical relation extraction

Autor: Joël Legrand, Yannick Toussaint, Chedy Raïssi, Adrien Coulet

Publikováno v: Journal of Biomedical Semantics, Vol 12, Iss 1, Pp 1-11 (2021)

Abstract Background Transfer learning aims at enhancing machine learning performance on a problem by reusing labeled data originally designed for a related, but distinct problem. In particular, domain adaptation consists for a specific task, in reusi

Externí odkaz: https://doaj.org/article/a2b21ad6ad8345ec8f0b65b1b53382f0

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Rapid classification of TESS planet candidates with convolutional neural networks

Autor: Jon M. Jenkins, Jeffrey C. Smith, Douglas A. Caldwell, Megan Ansdell, Yani Ioannou, Chedy Raïssi, Hugh P. Osborn, Daniel Angerhausen, Michele Sasdelli

Publikováno v: Osborn, H. P.; Ansdell, M.; Ioannou, Y.; Sasdelli, M.; Angerhausen, D.; Caldwell, D.; Jenkins, J. M.; Räissi, C.; Smith, J. C. (2020). Rapid classification of TESS planet candidates with convolutional neural networks. Astronomy and astrophysics, 633, A53. EDP Sciences 10.1051/0004-6361/201935345
Astronomy and Astrophysics-A&A
Astronomy and Astrophysics-A&A, 2020, 633, ⟨10.1051/0004-6361/201935345⟩
Astronomy & Astrophysics, 633

Aims. Accurately and rapidly classifying exoplanet candidates from transit surveys is a goal of growing importance as the data rates from space-based survey missions increase. This is especially true for the NASA TESS mission which generates thousand

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a4f8d427b1e862ec6d9573a48892baa7
https://boris.unibe.ch/142622/1/1902.08544.pdf

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Syntax-based Transfer Learning for the Task of Biomedical Relation Extraction

Autor: Yannick Toussaint, Adrien Coulet, Chedy Raïssi, Joël Legrand

Publikováno v: LOUHI 2018-The Ninth International Workshop on Health Text Mining and Information Analysis
LOUHI 2018-The Ninth International Workshop on Health Text Mining and Information Analysis, Oct 2018, Brussels, Belgium
HAL
Journal of Biomedical Semantics
Journal of Biomedical Semantics, BioMed Central, 2021, 12 (1), ⟨10.1186/s13326-021-00248-y⟩
Louhi@EMNLP
Journal of Biomedical Semantics, Vol 12, Iss 1, Pp 1-11 (2021)
Journal of Biomedical Semantics, 2021, 12 (1), ⟨10.1186/s13326-021-00248-y⟩

Background Transfer learning aims at enhancing machine learning performance on a problem by reusing labeled data originally designed for a related, but distinct problem. In particular, domain adaptation consists for a specific task, in reusing traini

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::007254817164c8f311412e2c8dc588cc
https://hal.inria.fr/hal-01869071/file/louhi-syntax-based(1).pdf

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Sequence Mining within Formal Concept Analysis for Analyzing Visitor Trajectories

Autor: Chedy Raïssi, Amedeo Napoli, Miguel Couceiro, Nyoman Juniarta

Publikováno v: SMAP 2018-13th International Workshop on Semantic and Social Media Adaptation and Personalization
SMAP 2018-13th International Workshop on Semantic and Social Media Adaptation and Personalization, Sep 2018, Zaragoza, Spain
SMAP

International audience; This paper presents our work about mining visitor trajectories, within the framework of CrossCult European Project about cultural heritage. We present a theoretical and practical research work about the characterization of vis

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::66bf7a14546d1af6ea756516a98b8463
https://inria.hal.science/hal-01887927/document

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Scientific Domain Knowledge Improves Exoplanet Transit Classification with Deep Learning

Autor: Jon M. Jenkins, Megan Ansdell, Yani Ioannou, Chedy Raïssi, Daniel Angerhausen, Jeffrey C. Smith, Michele Sasdelli, Hugh P. Osborn, Douglas A. Caldwell

Publikováno v: The Astrophysical journal letters
The Astrophysical journal letters, Bristol : IOP Publishing, 2018, 869 (1), pp.L7. ⟨10.3847/2041-8213/aaf23b⟩
The Astrophysical journal letters, 2018, 869 (1), pp.L7. ⟨10.3847/2041-8213/aaf23b⟩

Space-based missions such as Kepler, and soon TESS, provide large datasets that must be analyzed efficiently and systematically. Recent work by Shallue & Vanderburg (2018) successfully used state-of-the-art deep learning models to automatically class

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9715ae195604b725f2f6556b4db8937f

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Anytime Discovery of a Diverse Set of Patterns with Monte Carlo Tree Search

Autor: Jean-François Boulicaut, Chedy Raïssi, Mehdi Kaytoue, Guillaume Bosc

Publikováno v: Data Mining and Knowledge Discovery
Data Mining and Knowledge Discovery, Springer, 2018, 32 (3), pp.604-650. ⟨10.1007/s10618-017-0547-5⟩
Data Mining and Knowledge Discovery, 2018, 32 (3), pp.604-650. ⟨10.1007/s10618-017-0547-5⟩

The discovery of patterns that accurately discriminate one class label from another remains a challenging data mining task. Subgroup discovery (SD) is one of the frameworks that enables to elicit such interesting hypotheses from labeled data. A quest

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e9491f0c576b1a5a9c10fd0bb60f360
https://hal.archives-ouvertes.fr/hal-01662857v2/document

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On mining complex sequential data by means of FCA and pattern structures

Autor: Elias Egho, Amedeo Napoli, Nicolas Jay, Sergei O. Kuznetsov, Aleksey Buzmakov, Chedy Raïssi

Publikováno v: International Journal of General Systems
International Journal of General Systems, 2016, 45 (2), pp.135-159. ⟨10.1080/03081079.2015.1072925⟩
International Journal of General Systems, Taylor & Francis, 2016, 45 (2), pp.135-159. ⟨10.1080/03081079.2015.1072925⟩

Nowadays data sets are available in very complex and heterogeneous ways. Mining of such data collections is essential to support many real-world applications ranging from healthcare to marketing. In this work, we focus on the analysis of "complex" se

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8af49ffac1166525f68b8eb3dd7876b4
https://doi.org/10.1080/03081079.2015.1072925

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Two-phase preference disclosure in attributed social networks

Autor: Abdessamad Imine, Michaël Rusinowitch, Chedy Raïssi, Amedeo Napoli, Younes Abid

Publikováno v: DEXA 2017-28th International Conference on Database and Expert Systems Applications
DEXA 2017-28th International Conference on Database and Expert Systems Applications, Aug 2017, Lyon, France. pp.249-263, ⟨10.1007/978-3-319-64468-4_19⟩
Lecture Notes in Computer Science ISBN: 9783319644677
DEXA (1)

International audience; In order to demonstrate privacy threats in social networks we show how to infer user preferences by random walks in a multiple graph representing simultaneously attributes and relationships links. For the approach to scale in

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf464c7b64ea0176b87c651421573219
https://inria.hal.science/hal-01649246/document

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A Pattern Mining Approach to Study Strategy Balance in RTS Games

Autor: Guillaume Bosc, Jean-François Boulicaut, Chedy Raïssi, Mehdi Kaytoue, Philip Tan

Publikováno v: IEEE Transactions on Computational Intelligence and AI in games
IEEE Transactions on Computational Intelligence and AI in games, 2017, 9 (2), pp.123-132. ⟨10.1109/TCIAIG.2015.2511819⟩
IEEE Transactions on Computational Intelligence and AI in games, IEEE Computational Intelligence Society, 2017, 9 (2), pp.123-132. ⟨10.1109/TCIAIG.2015.2511819⟩

International audience; Whereas purest strategic games such as Go and Chess seem timeless, the lifetime of a video game is short, influenced by popular culture, trends, boredom and technological innovations. Even the important budget and de- velopmen

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::012fbe0f7acf6f4afa604d10f04a3e46
https://hal.science/hal-01252728

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Autor: Toon Calders, Nicolas Jay, Amedeo Napoli, Elias Egho, Chedy Raïssi

Publikováno v: Data Mining and Knowledge Discovery
Data Mining and Knowledge Discovery, Springer, 2015, 29 (3), pp.33. ⟨10.1007/s10618-014-0362-1⟩
Data Mining and Knowledge Discovery, 2015, 29 (3), pp.33. ⟨10.1007/s10618-014-0362-1⟩

International audience; Computing the similarity between sequences is a very important challenge for many different data mining tasks. There is a plethora of similarity measures for sequences in the literature, most of them being designed for sequenc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d177077139418c155b647165ce63f0a0
https://doi.org/10.1007/s10618-014-0362-1

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