Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Véronique Masson"'
Publikováno v:
Mathematics, Vol 9, Iss 23, p 3137 (2021)
Multivariate Time Series (MTS) classification has gained importance over the past decade with the increase in the number of temporal datasets in multiple domains. The current state-of-the-art MTS classifier is a heavyweight deep learning approach, wh
Externí odkaz:
https://doaj.org/article/a7cf2d41940e4301b88c3ab2908ef9f6
Autor:
Dante Rotili, Domenico Tarantino, Biagina Marrocco, Christina Gros, Véronique Masson, Valérie Poughon, Fréderic Ausseil, Yanqi Chang, Donatella Labella, Sandro Cosconati, Salvatore Di Maro, Ettore Novellino, Michael Schnekenburger, Cindy Grandjenette, Celine Bouvy, Marc Diederich, Xiaodong Cheng, Paola B Arimondo, Antonello Mai
Publikováno v:
PLoS ONE, Vol 9, Iss 5, p e96941 (2014)
Chemical manipulations performed on the histone H3 lysine 9 methyltransferases (G9a/GLP) inhibitor BIX-01294 afforded novel desmethoxyquinazolines able to inhibit the DNA methyltransferase DNMT3A at low micromolar levels without any significant inhib
Externí odkaz:
https://doaj.org/article/281a01d650e04497b3316ad698b79eb4
Publikováno v:
Data Mining and Knowledge Discovery
Data Mining and Knowledge Discovery, 2022, 36 (3), pp.917-957. ⟨10.1007/s10618-022-00823-6⟩
Data Mining and Knowledge Discovery, 2022, 36 (3), pp.917-957. ⟨10.1007/s10618-022-00823-6⟩
We present XEM, an eXplainable-by-design Ensemble method for Multivariate time series classification. XEM relies on a new hybrid ensemble method that combines an explicit boosting-bagging approach to handle the bias-variance trade-off faced by machin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cb807d9d37ac476d0022952eb845758e
https://hal.inria.fr/hal-03599214
https://hal.inria.fr/hal-03599214
Autor:
Véronique Masson, Alexandre Carpentier, Insafe Mezjan, Isabelle Gourfinkel-An, Stéphane Clemenceau, Vincent Navarro, Vincent Degos, Bertrand Mathon
Publikováno v:
Epilepsybehavior : EB. 118
Purpose Vagus nerve stimulation (VNS) implantation is increasingly proposed in outpatient procedure. Some epilepsy syndromes are associated with severe neurodevelopmental disabilities (intellectual disability, autism) and often motor or sensory handi
Publikováno v:
In Proceedings of the IJCAI-PRICAI 2020 Workshop on Explainable AI
In Proceedings of the IJCAI-PRICAI 2020 Workshop on Explainable AI, Jan 2021, Yokohama, Japan. pp.1-8
IJCAI-PRICAI 2020-Workshop on Explainable Artificial Intelligence (XAI)
IJCAI-PRICAI 2020-Workshop on Explainable Artificial Intelligence (XAI), Jan 2021, Yokohama, Japan. pp.1-8
HAL
In Proceedings of the IJCAI-PRICAI 2020 Workshop on Explainable AI, Jan 2021, Yokohama, Japan. pp.1-8
IJCAI-PRICAI 2020-Workshop on Explainable Artificial Intelligence (XAI)
IJCAI-PRICAI 2020-Workshop on Explainable Artificial Intelligence (XAI), Jan 2021, Yokohama, Japan. pp.1-8
HAL
Our research aims to propose a new performance-explainability analytical framework to assess and benchmark machine learning methods. The framework details a set of characteristics that systematize the performance-explainability assessment of existing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dc2aa6a92c1072e01dec71ab93fd4bc3
https://hal.archives-ouvertes.fr/hal-03094885
https://hal.archives-ouvertes.fr/hal-03094885
Publikováno v:
ICTAI 2019-31st International Conference on Tools with Artificial Intelligence
ICTAI 2019-31st International Conference on Tools with Artificial Intelligence, Nov 2019, Portland, United States
ICTAI
ICTAI 2019-31st International Conference on Tools with Artificial Intelligence, Nov 2019, Portland, United States
ICTAI
Recent advances in Machine Learning (such as Deep Learning) have brought tremendous gains in classification accuracy. However, these approaches build complex non-linear models, making the resulting predictions difficult to interpret for humans. The f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::070259b2c2d13bce767ddadef77bbf3c
https://inria.hal.science/hal-02460955
https://inria.hal.science/hal-02460955
Publikováno v:
In Proceedings of the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
In Proceedings of the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Aug 2019, Anchorage, United States. pp.3051-3059, ⟨10.1145/3292500.3330712⟩
KDD 2019-ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
KDD 2019-ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, Aug 2019, Anchorage, United States. pp.1-9, ⟨10.1145/3292500.3330712⟩
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2019; KDD'19, Anchorage, USA, 2019-08-04-2019-08-08, 3051-3059
KDD
In Proceedings of the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Aug 2019, Anchorage, United States. pp.3051-3059, ⟨10.1145/3292500.3330712⟩
KDD 2019-ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
KDD 2019-ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, Aug 2019, Anchorage, United States. pp.1-9, ⟨10.1145/3292500.3330712⟩
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2019; KDD'19, Anchorage, USA, 2019-08-04-2019-08-08, 3051-3059
KDD
International audience; Our research tackles the challenge of milk production resource use efficiency in dairy farms with machine learning methods. Reproduction is a key factor for dairy farm performance since cows milk production begin with the birt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a5433e0efd4d966e202f32a0db2fc144
https://hal.science/hal-02190790
https://hal.science/hal-02190790
Publikováno v:
One-day Workshop on Machine Learning and Explainability
One-day Workshop on Machine Learning and Explainability, Christel Vrain, Université d' Orléans, Oct 2018, Orléans, France
ICTAI 2019-31st International Conference on Tools with Artificial Intelligence
ICTAI 2019-31st International Conference on Tools with Artificial Intelligence, Nov 2019, Portland, United States. pp.1480-1485
ICTAI
One-day Workshop on Machine Learning and Explainability, Christel Vrain, Université d' Orléans, Oct 2018, Orléans, France
ICTAI 2019-31st International Conference on Tools with Artificial Intelligence
ICTAI 2019-31st International Conference on Tools with Artificial Intelligence, Nov 2019, Portland, United States. pp.1480-1485
ICTAI
Rule learning is a data analysis task consisting of extracting rules to generalize examples. For a data scientist, some generalizations called here admissible generalizations, make more sense. We explore formal properties of admissible generalization
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::557574e419371b1f63951130f9c6fb72
https://hal.inria.fr/hal-01940129
https://hal.inria.fr/hal-01940129
Autor:
Yoann Menon, Christina Gros, Philippe Schambel, Véronique Masson, Paola B. Arimondo, Alexandre Erdmann, Yannick Aussagues, Michel Baltas, Frédéric Ausseil, Natacha Novosad
Publikováno v:
Future Medicinal Chemistry
Future Medicinal Chemistry, 2016, 8 (4), pp.373-380. ⟨10.4155/fmc.15.192⟩
Future Medicinal Chemistry, Future Science, 2016, 8 (4), pp.373-380. ⟨10.4155/fmc.15.192⟩
Future Medicinal Chemistry, 2016, 8 (4), pp.373-380. ⟨10.4155/fmc.15.192⟩
Future Medicinal Chemistry, Future Science, 2016, 8 (4), pp.373-380. ⟨10.4155/fmc.15.192⟩
DNA methylation is the most studied epigenetic event. Since the methylation profile of the genome is widely modified in cancer cells, DNA methyltransferases are the target of new anticancer therapies. Nucleosidic inhibitors suffer from toxicity and c
Publikováno v:
Epilepsy & Behavior
Epilepsy & Behavior, [San Diego CA]: Elsevier B.V., 2018, 81, pp.49-54. ⟨10.1016/j.yebeh.2017.11.018⟩
Epilepsy & Behavior, 2018, 81, pp.49-54. ⟨10.1016/j.yebeh.2017.11.018⟩
Epilepsy & Behavior, [San Diego CA]: Elsevier B.V., 2018, 81, pp.49-54. ⟨10.1016/j.yebeh.2017.11.018⟩
Epilepsy & Behavior, 2018, 81, pp.49-54. ⟨10.1016/j.yebeh.2017.11.018⟩
International audience; Objective : The objective of this study was to test the reliability of functional magnetic resonance imaging (fMRI) evaluation of memory function in clinical practice to predict postoperative memory decline in patients with re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5c3bfee50cbf043327f6bde4b843711
https://hal.sorbonne-universite.fr/hal-01741854
https://hal.sorbonne-universite.fr/hal-01741854