Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Hanane Azzag"'
Publikováno v:
In Procedia Computer Science 2018 144:239-250
Publikováno v:
Advances in Knowledge Discovery and Data Mining ISBN: 9783031333736
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::228e871be9aca4143c23f35adf2cedbd
https://doi.org/10.1007/978-3-031-33374-3_17
https://doi.org/10.1007/978-3-031-33374-3_17
Publikováno v:
Computational Statistics & Data Analysis. 176:107565
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::612cbc74ab88b8280a7845158d577c63
https://doi.org/10.1016/j.csda.2022.107565
https://doi.org/10.1016/j.csda.2022.107565
This book constitutes the proceedings of the 27th International Symposium on Methodologies for Intelligent Systems, ISMIS 2024, held in Poitiers, France, in June 2024. The 18 full papers, 6 short papers and 5 industrial papers presented in this vo
Publikováno v:
ICPR
Time series clustering is a challenging task due to the specificities of this type of data. Temporal correlation and invariance to transformations such as shifting, warping or noise prevent the use of standard data mining methods. Time series cluster
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::89975c2c03bb2c1ad2a5cf82888cabe3
https://doi.org/10.1109/icpr48806.2021.9412020
https://doi.org/10.1109/icpr48806.2021.9412020
Publikováno v:
ESANN 2021 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Oct 2021, Online, France
European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Oct 2021, Online, France
International audience; Driver assistance systems development remains a technical challenge for car manufacturers. Validating these systems requires to assess the assistance systems performances in a considerable number of driving contexts. Groupe Re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4aeab5fd599325f3f504e2bc8e65ae31
https://doi.org/10.14428/esann/2021.es2021-119
https://doi.org/10.14428/esann/2021.es2021-119
Publikováno v:
Advanced Analytics and Learning on Temporal Data ISBN: 9783030914448
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de402e27e3951bc7e2fed1f10ec6932c
https://doi.org/10.1007/978-3-030-91445-5_5
https://doi.org/10.1007/978-3-030-91445-5_5
Publikováno v:
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML PKDD.
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML PKDD., Sep 2020, Ghent, Belgium
Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track ISBN: 9783030676667
ECML/PKDD (4)
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML PKDD., Sep 2020, Ghent, Belgium
Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track ISBN: 9783030676667
ECML/PKDD (4)
International audience; Validation of autonomous driving systems remains one of the biggest challenges that car manufacturers must tackle in order to provide safe driverless cars. The complexity of this task stems from several factors: the multiplici
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b81cf6bd6b66a867a6caad7698ef77ae
https://hal.science/hal-03544495
https://hal.science/hal-03544495
In this paper we target the class of modal clustering methods where clusters are defined in terms of the local modes of the probability density function which generates the data. The most well-known modal clustering method is the k-means clustering.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c7752e289b87778e19f2c60790e9a8bc
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030261412
PAKDD (Workshops)
PAKDD (Workshops)
Recent research has demonstrated how deep neural networks are able to learn representations to improve data clustering. By considering representation learning and clustering as a joint task, models learn clustering-friendly spaces and achieve superio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a39d211bc63bc2a85f1ea164ee3b49f2
https://doi.org/10.1007/978-3-030-26142-9_10
https://doi.org/10.1007/978-3-030-26142-9_10