Zobrazeno 1 - 10
of 57
pro vyhledávání: '"Ilia, Nouretdinov"'
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8ea82598ae6867f83600569362a7dde4
https://doi.org/10.25046/aj020335
https://doi.org/10.25046/aj020335
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a5dbe5d2ddb0f450ff42bf134cdce5a8
https://doi.org/10.1016/j.procs.2017.08.314
https://doi.org/10.1016/j.procs.2017.08.314
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
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319945224
ICOST
ICOST
The aim of this work is to discuss abnormality detection and explanation challenges motivated by Medical Internet of Things. First, any feature is a measurement taken by a sensor at a time moment, so abnormality detection also becomes a sequential pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9461b4c7b39d23bd221fe29096a4e3e9
https://doi.org/10.1007/978-3-319-94523-1_31
https://doi.org/10.1007/978-3-319-94523-1_31
Publikováno v:
Braverman Readings in Machine Learning. Key Ideas from Inception to Current State ISBN: 9783319994918
Braverman Readings in Machine Learning
Braverman Readings in Machine Learning
This paper reviews the checkered history of predictive distributions in statistics and discusses two developments, one from recent literature and the other new. The first development is bringing predictive distributions into machine learning, whose e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::af98114574eb435ddf9f5c8f3211a54f
https://doi.org/10.1007/978-3-319-99492-5_4
https://doi.org/10.1007/978-3-319-99492-5_4
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319945224
ICOST
ICOST
Medical and general health-related measurements can increasingly be performed via IoT components and protocols, whilst inexpensive sensors allow the capturing of a wider range of parameters in clinical, care, and general health monitoring domains. Me
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b9e939fdece24b0781e42fb3448cdae6
https://doi.org/10.1007/978-3-319-94523-1_13
https://doi.org/10.1007/978-3-319-94523-1_13
Publikováno v:
Annals of Mathematics and Artificial Intelligence
The paper presents an application of Conformal Predictors to a chemoinformatics problem of predicting the biological activities of chemical compounds. The paper addresses some specific challenges in this domain: a large number of compounds (training
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fdfd22f7f79e6bd0bd2c23960e9c1af8
Publikováno v:
Annals of Mathematics and Artificial Intelligence. 74:181-201
Venn Predictors (VPs) are machine learning algorithms that can provide well calibrated multiprobability outputs for their predictions. An important drawback of Venn Predictors is their computational inefficiency, especially in the case of large datas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::db973026c0555183f50081fc36566d06
https://doi.org/10.1007/s10472-014-9420-z
https://doi.org/10.1007/s10472-014-9420-z