Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Fauvel, Kevin"'
lcensemble is a high-performing, scalable and user-friendly Python package for the general tasks of classification and regression. The package implements Local Cascade Ensemble (LCE), a machine learning method that further enhances the prediction per
Externí odkaz:
http://arxiv.org/abs/2308.07250
Traffic classification, i.e. the identification of the type of applications flowing in a network, is a strategic task for numerous activities (e.g., intrusion detection, routing). This task faces some critical challenges that current deep learning ap
Externí odkaz:
http://arxiv.org/abs/2202.05535
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:
http://arxiv.org/abs/2009.04796
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:
http://arxiv.org/abs/2005.14501
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:
http://arxiv.org/abs/2005.03645
Akademický článek
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Autor:
Harada, Issei, Fauvel, Kevin, Guyet, Thomas, Masson, Véronique, Termier, Alexandre, Faverdin, Philippe
Publikováno v:
Proceedings of the 36th AAAI Conference on Artificial Intelligence. Workshop
AAAI 2022-36th AAAI Conference on Artificial Intelligence
AAAI 2022-36th AAAI Conference on Artificial Intelligence, Feb 2022, Vancouver, Canada. pp.1-10
36th AAAI Conference on Artificial Intelligence. Workshop
36th AAAI Conference on Artificial Intelligence. Workshop, Feb 2022, Vancouver, Canada
AAAI 2022-36th Conference on Artificial Intelligence. Workshop
AAAI 2022-36th Conference on Artificial Intelligence. Workshop, Feb 2022, Vancouver, Canada
In Proceedings of the 36th AAAI Conference on Artificial Intelligence. Workshop
In Proceedings of the 36th AAAI Conference on Artificial Intelligence. Workshop, Feb 2022, Vancouver, Canada
AAAI 2022-36th AAAI Conference on Artificial Intelligence
AAAI 2022-36th AAAI Conference on Artificial Intelligence, Feb 2022, Vancouver, Canada. pp.1-10
36th AAAI Conference on Artificial Intelligence. Workshop
36th AAAI Conference on Artificial Intelligence. Workshop, Feb 2022, Vancouver, Canada
AAAI 2022-36th Conference on Artificial Intelligence. Workshop
AAAI 2022-36th Conference on Artificial Intelligence. Workshop, Feb 2022, Vancouver, Canada
In Proceedings of the 36th AAAI Conference on Artificial Intelligence. Workshop
In Proceedings of the 36th AAAI Conference on Artificial Intelligence. Workshop, Feb 2022, Vancouver, Canada
International audience; A powerful automatic detection of estrus, the only period when the cow is susceptible to pregnancy, is a key driver to help farmers with reproduction management and subsequently to improve milk production resource use in dairy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::f022ad73ed54a20afbbf7f4de6b110bd
https://hal.inria.fr/hal-03483109v2/file/Harada22_XPM.pdf
https://hal.inria.fr/hal-03483109v2/file/Harada22_XPM.pdf
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
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Autor:
Balouek-Thomert, Daniel, Silva, Pedro, Fauvel, Kevin, Costan, Alexandru, Antoniu, Gabriel, Parashar, Manish
Publikováno v:
DML-ICC 2021 workshop (held in conjunction with UCC 2021)
DML-ICC 2021 workshop (held in conjunction with UCC 2021), Dec 2021, Leicester, United Kingdom
DML-ICC 2021 workshop (held in conjunction with UCC 2021), Dec 2021, Leicester, United Kingdom
International audience; The growth of the Internet of Things is resulting in an explosion of data volumes at the Edge of the Internet. To reduce costs incurred due to data movement and centralized cloud-based processing, it is becoming increasingly i
Autor:
Balouek-Thomert, Daniel, Silva, Pedro, Fauvel, Kevin, Costan, Alexandru, Antoniu, Gabriel, Parashar, Manish
Publikováno v:
LCN 2021-46th IEEE Conference on Local Computer Networks
LCN 2021-46th IEEE Conference on Local Computer Networks, Oct 2021, Edmonton, Canada. pp.185-192, ⟨10.1109/LCN52139.2021.9524880⟩
LCN
LCN 2021-46th IEEE Conference on Local Computer Networks, Oct 2021, Edmonton, Canada. pp.185-192, ⟨10.1109/LCN52139.2021.9524880⟩
LCN
International audience; Monitoring the status of network slices is a priority for network operators to ensure that SLAs are not violated. To overcome the limitations of direct slices' monitoring, network tomography (NT) is seen as a promising solutio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::776869e446ca2e0a45d03c0cd8db0bb7
https://inria.hal.science/hal-03510074/file/Cycle_probing.pdf
https://inria.hal.science/hal-03510074/file/Cycle_probing.pdf