Zobrazeno 1 - 10
of 136
pro vyhledávání: '"Ilia, Nouretdinov"'
Publikováno v:
Advances in Science, Technology and Engineering Systems Journal. 2:553-561
Publikováno v:
Advances in Science, Technology and Engineering Systems Journal. 2:291-301
Autor:
Sarra Alqahtani, Rose Gamble
Publikováno v:
Advances in Science, Technology and Engineering Systems Journal. 2:449-459
Autor:
Fatma Abdelhedi, Nabil Derbel
Publikováno v:
Advances in Science, Technology and Engineering Systems Journal. 2:513-519
Autor:
Leon Bottou, Bernard Goldfarb, Mirelle Summa, Myriam Touati, Flonn Murtagh, Catherine Pardoux
Publikováno v:
Statistical Learning and Data Science
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9ac49e2c81e9c713510f89401d6d295
https://doi.org/10.1201/b11429-8
https://doi.org/10.1201/b11429-8
Autor:
Ilia Nouretdinov
Publikováno v:
Advances in Science, Technology and Engineering Systems Journal
Advances in Science, Technology and Engineering Systems, Vol 2, Iss 3, Pp 254-267 (2017)
Advances in Science, Technology and Engineering Systems, Vol 2, Iss 3, Pp 254-267 (2017)
Conformal Prediction is a recently developed framework for reliable confident predictions. In this work we discuss its possible application to big data coming from different, possibly heterogeneous data sources. On example of anomaly detection proble
Publikováno v:
EUSPN/ICTH
The Medical Internet of Things (MIoT) has applications beyond clinical settings including in outpatient and care environments where monitoring is occurring over public networks and may involve non-dedicated devices. This poses a number of security an
Conformal predictive systems are a recent modification of conformal predictors that output, in regression problems, probability distributions for labels of test observations rather than set predictions. The extra information provided by conformal pre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::67f253395c6ea1c1543f767c04b20c52
http://arxiv.org/abs/1911.00941
http://arxiv.org/abs/1911.00941
Multi-level conformal clustering: A distribution-free technique for clustering and anomaly detection
In this work we present a clustering technique called multi-level conformal clustering (MLCC). The technique is hierarchical in nature because it can be performed at multiple significance levels which yields greater insight into the data than perform
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::615f15c709f71ab27529bf95b71a1785
http://arxiv.org/abs/1910.08105
http://arxiv.org/abs/1910.08105
Publikováno v:
Security and Privacy Trends in the Industrial Internet of Things ISBN: 9783030123291
Security and Privacy Trends in the Industrial Internet of Thing
Security and Privacy Trends in the Industrial Internet of Thing
Some type of privacy-preserving transformation must be applied to any data record from Industrial Internet of Things (IIoT) before it is disclosed to the researchers or analysts. Based on the existing privacy models such as Differential Privacy (DP)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ddb61211be0c240b16e94a71857a96c
https://doi.org/10.1007/978-3-030-12330-7_11
https://doi.org/10.1007/978-3-030-12330-7_11