Zobrazeno 1 - 10
of 88
pro vyhledávání: '"Christel Vrain"'
Publikováno v:
Data in Brief, Vol 57, Iss , Pp 110893- (2024)
Deep learning applied to raw data has demonstrated outstanding image classification performance, mainly when abundant data is available. However, performance significantly degrades when a substantial volume of data is unavailable. Furthermore, deep a
Externí odkaz:
https://doaj.org/article/6317224c24c845d3b29d5527e2dd9bc4
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783031263866
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::721c5ace638e9dd67b48e13d34e65899
https://doi.org/10.1007/978-3-031-26387-3_11
https://doi.org/10.1007/978-3-031-26387-3_11
Publikováno v:
Pattern Recognition and Artificial Intelligence ISBN: 9783031090363
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f6507c910ba452da4d04083066f93dca
https://doi.org/10.1007/978-3-031-09037-0_53
https://doi.org/10.1007/978-3-031-09037-0_53
Publikováno v:
HAL
In the context of semi-supervised learning and clustering ensemble methods, we introduce a novel strategy to consider not only pairwise constraints, but also triplet constraints. As far as we are aware, the latter have not been addressed in the liter
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::790ce81a4ba18726d7d82a9fe79a70c6
https://hal.science/hal-03672982
https://hal.science/hal-03672982
Autor:
Thomas Lampert, Pierre Gançarski, Baptiste Lafabregue, Nicolas Serrette, Thi-Bich-Hanh Dao, Christel Vrain
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019, 12 (11), pp.4606-4621. ⟨10.1109/JSTARS.2019.2950406⟩
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 2019, 12 (11), pp.4606-4621. ⟨10.1109/JSTARS.2019.2950406⟩
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019, 12 (11), pp.4606-4621. ⟨10.1109/JSTARS.2019.2950406⟩
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 2019, 12 (11), pp.4606-4621. ⟨10.1109/JSTARS.2019.2950406⟩
International audience; The advent of high-resolution instruments for time-series sampling poses added complexity for the formal definition of thematic classes in the remote sensing domain-required by supervised methods-while unsupervised methods ign
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e6ff36b54a7a1fca70aba9c247b7efa
https://doi.org/10.1109/jstars.2019.2950406
https://doi.org/10.1109/jstars.2019.2950406
Publikováno v:
Machine Learning
Machine Learning, 2019, 108 (7), pp.1057-1059. ⟨10.1007/s10994-019-05790-6⟩
Machine Learning, 2019, 108 (7), pp.1057-1059. ⟨10.1007/s10994-019-05790-6⟩
Inductive Logic Programming (ILP) is a field at the intersection of Machine Learning and Logic Programming, based on logic as a uniform representation language for expressing examples, background knowledge and hypotheses.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::54cc886989490b94ec54e3e1e4674191
https://hal.science/hal-03701326
https://hal.science/hal-03701326
Publikováno v:
IJCAI-ECAI 2018, the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence
IJCAI-ECAI 2018, the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence, Jul 2018, Stockholm, Sweden
HAL
IJCAI-ECAI 2018, the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence, Jul 2018, Stockholm, Sweden
HAL
International audience
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::8e1a5dcdd2bcce43099878816d5bc875
https://hal.archives-ouvertes.fr/hal-01784499
https://hal.archives-ouvertes.fr/hal-01784499
Publikováno v:
IJCAI
In many settings just finding a good clustering is insufficient and an explanation of the clustering is required. If the features used to perform the clustering are interpretable then methods such as conceptual clustering can be used. However, in man
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cdcde47187847b2aac40c5dc467850b2
https://doi.org/10.24963/ijcai.2018/176
https://doi.org/10.24963/ijcai.2018/176
Autor:
Germain Forestier, Christel Vrain, Nicolas Serrette, Baptiste Lafabregue, Thi-Bich-Hanh Dao, Pierre Gançarski, Bruno Crémilleux, Thomas Lampert
Publikováno v:
Data Mining and Knowledge Discovery
Data Mining and Knowledge Discovery, 2018, 32 (6), pp.1663-1707. ⟨10.1007/s10618-018-0573-y⟩
Data Mining and Knowledge Discovery, Springer, 2018, 32 (6), pp.1663-1707. ⟨10.1007/s10618-018-0573-y⟩
Data Mining and Knowledge Discovery, 2018, 32 (6), pp.1663-1707. ⟨10.1007/s10618-018-0573-y⟩
Data Mining and Knowledge Discovery, Springer, 2018, 32 (6), pp.1663-1707. ⟨10.1007/s10618-018-0573-y⟩
International audience; Constrained clustering is becoming an increasingly popular approach in data mining. It offers a balance between the complexity of producing a formal definition of thematic classes-required by supervised methods-and unsupervise
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7daacee79c15b3142c0105e27f7b1e78
https://hal.science/hal-01831637/document
https://hal.science/hal-01831637/document
Autor:
Nicolas Lachiche, Christel Vrain
This book constitutes the thoroughly refereed post-conference proceedings of the 27th International Conference on Inductive Logic Programming, ILP 2017, held in Orléans, France, in September 2017. The 12 full papers presented were carefully reviewed