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pro vyhledávání: '"Naumzik, Christof"'
Clinical data informs the personalization of health care with a potential for more effective disease management. In practice, this is achieved by subgrouping, whereby clusters with similar patient characteristics are identified and then receive custo
Externí odkaz:
http://arxiv.org/abs/2404.10580
In order to deliver effective care, health management must consider the distinctive trajectories of chronic diseases. These diseases recurrently undergo acute, unstable, and stable phases, each of which requires a different treatment regimen. However
Externí odkaz:
http://arxiv.org/abs/2206.00953
The availability of charging stations is an important factor for promoting electric vehicles (EVs) as a carbon-friendly way of transportation. Hence, for city planners, the crucial question is where to place charging stations so that they reach a lar
Externí odkaz:
http://arxiv.org/abs/2203.07081
Autor:
Naumzik, Christof, Feuerriegel, Stefan
False rumors are known to have detrimental effects on society. To prevent the spread of false rumors, social media platforms such as Twitter must detect them early. In this work, we develop a novel probabilistic mixture model that classifies true vs.
Externí odkaz:
http://arxiv.org/abs/2201.13103
Autor:
Naumzik, Christof, Feuerriegel, Stefan
Purpose: Trading on electricity markets occurs such that the price settlement takes place before delivery, often day-ahead. In practice, these prices are highly volatile as they largely depend upon a range of variables such as electricity demand and
Externí odkaz:
http://arxiv.org/abs/2005.08005
Publikováno v:
In European Journal of Operational Research 1 March 2023 305(2):853-867
Autor:
Naumzik, Christof, Feuerriegel, Stefan
Publikováno v:
International Journal of Energy Sector Management, 2020, Vol. 15, Issue 1, pp. 157-172.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJESM-01-2020-0001
Akademický článek
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Publikováno v:
Proceedings of the World Wide Web Conference 2020 (WWW '20)
Points-of-interest (POIs; i.e., restaurants, bars, landmarks, and other entities) are common in web-mined data: they greatly explain the spatial distributions of urban phenomena. The conventional modeling approach relies upon feature engineering, yet
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d41c0fdeba71a8bd572c90367a949e3d