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pro vyhledávání: '"Popovski, Gorjan"'
Accurately predicting the performance of different optimization algorithms for previously unseen problem instances is crucial for high-performing algorithm selection and configuration techniques. In the context of numerical optimization, supervised r
Externí odkaz:
http://arxiv.org/abs/2104.10999
Automated algorithm selection and configuration methods that build on exploratory landscape analysis (ELA) are becoming very popular in Evolutionary Computation. However, despite a significantly growing number of applications, the underlying machine
Externí odkaz:
http://arxiv.org/abs/2104.09272
Automated per-instance algorithm selection and configuration have shown promising performances for a number of classic optimization problems, including satisfiability, AI planning, and TSP. The techniques often rely on a set of features that measure
Externí odkaz:
http://arxiv.org/abs/2009.14506
Autor:
Emara, Yasmine, Koroušić Seljak, Barbara, Gibney, Eileen R., Popovski, Gorjan, Pravst, Igor, Fantke, Peter
Publikováno v:
In Trends in Food Science & Technology May 2022 123:310-321
Publikováno v:
In Big Data Research 15 July 2021 25
Publikováno v:
In Food and Chemical Toxicology April 2020 138
Publikováno v:
Trends in Food Science & Technology
Background: The COVID-19 pandemic affects all aspects of human life including their food consumption. The changes in the food production and supply processes introduce changes to the global dietary patterns. Scope and Approach: To study the COVID-19
Publikováno v:
In Trends in Food Science & Technology January 2021 107:183-194
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An overview and a comparison of named-entity recognition methods in the food domain, which can be used for automated extraction of food information from text.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2659::44796964e26688ea8696e4867d603e8f
https://zenodo.org/record/6951899
https://zenodo.org/record/6951899