Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Tea Tusar"'
Publikováno v:
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation, 2022, 26 (6), pp.1293--1305. ⟨10.1109/TEVC.2022.3210897⟩
IEEE Transactions on Evolutionary Computation, 2022, 26 (6), pp.1293--1305. ⟨10.1109/TEVC.2022.3210897⟩
open access; International audience; We present concepts and recipes for the anytime performance assessment when benchmarking optimization algorithms in a blackbox scenario. We consider runtime-oftentimes measured in number of blackbox evaluations ne
Autor:
Michael Affenzeller, Stephan M. Winkler, Anna V. Kononova, Heike Trautmann, Tea Tušar, Penousal Machado, Thomas Bäck
This multi-volume LNCS set, LNCS 15148-15151, constitutes the refereed proceedings of the 18th International Conference on Parallel Problem Solving from Nature, PPSN 2024, held in Hagenberg, Austria, in September 2024. The 101 full papers presented i
This two-volume set LNCS 13398 and LNCS 13399 constitutes the refereed proceedings of the 17th International Conference on Parallel Problem Solving from Nature, PPSN 2022, held in Dortmund, Germany, in September 2022.The 87 revised full papers were c
Optimizing non-pharmaceutical intervention strategies against COVID-19 using artificial intelligence
Autor:
Vito Janko, Nina Reščič, Aljoša Vodopija, David Susič, Carlo De Masi, Tea Tušar, Anton Gradišek, Sophie Vandepitte, Delphine De Smedt, Jana Javornik, Matjaž Gams, Mitja Luštrek
Publikováno v:
Frontiers in Public Health, Vol 11 (2023)
One key task in the early fight against the COVID-19 pandemic was to plan non-pharmaceutical interventions to reduce the spread of the infection while limiting the burden on the society and economy. With more data on the pandemic being generated, it
Externí odkaz:
https://doaj.org/article/c65cce4036af4b26b368f5d206f49111
Autor:
Ouassim Ait El Hara, Dimo Brockhoff, Nikolaus Hansen, Konstantinos Varelas, Duc Manh Nguyen, Anne Auger, Tea Tušar
Publikováno v:
Applied Soft Computing
Applied Soft Computing, Elsevier, 2020, 97 (A), pp.106737. ⟨10.1016/j.asoc.2020.106737⟩
Applied Soft Computing, 2020, 97 (A), pp.106737. ⟨10.1016/j.asoc.2020.106737⟩
Applied Soft Computing, Elsevier, 2020, 97 (A), pp.106737. ⟨10.1016/j.asoc.2020.106737⟩
Applied Soft Computing, 2020, 97 (A), pp.106737. ⟨10.1016/j.asoc.2020.106737⟩
International audience; Benchmarking of optimization solvers is an important and compulsory task for performance assessment that in turn can help in improving the design of algorithms. It is a repetitive and tedious task. Yet, this task has been grea