Zobrazeno 1 - 10 of 58 pro vyhledávání: '"Jakob Bossek"'
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Akademický článek
Process-Oriented Stream Classification Pipeline: A Literature Review
Autor: Lena Clever, Janina Susanne Pohl, Jakob Bossek, Pascal Kerschke, Heike Trautmann
Publikováno v: Applied Sciences, Vol 12, Iss 18, p 9094 (2022)
Due to the rise of continuous data-generating applications, analyzing data streams has gained increasing attention over the past decades. A core research area in stream data is stream classification, which categorizes or detects data points within an
Externí odkaz: https://doaj.org/article/4cda206ef79444c7857058a233eec83c
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3
On the potential of automated algorithm configuration on multi-modal multi-objective optimization problems
Autor: Jeroen Rook, Heike Trautmann, Jakob Bossek, Christian Grimme
Publikováno v: GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion, 356-359
STARTPAGE=356;ENDPAGE=359;TITLE=GECCO '22
Hardness of Multi-Objective (MO) continuous optimization problems results from an interplay of various problem characteristics, e.g. the degree of multi-modality. We present a benchmark study of classical and diversity focused optimizers on multi-mod
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::efa7f281d6096b3ae19a1eb3ae96b786
https://doi.org/10.1145/3520304.3528998
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8
Time complexity analysis of randomized search heuristics for the dynamic graph coloring problem
Autor: Pan Peng, Frank Neumann, Jakob Bossek, Dirk Sudholt
We contribute to the theoretical understanding of randomized search heuristics for dynamic problems. We consider the classical vertex coloring problem on graphs and investigate the dynamic setting where edges are added to the current graph. We then a
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f018b481e6cc2da096b429ae9415af9c
https://eprints.whiterose.ac.uk/178846/1/Bossek2021_Article_TimeComplexityAnalysisOfRandom.pdf
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9
Do additional optima speed up evolutionary algorithms?
Autor: Dirk Sudholt, Jakob Bossek
Publikováno v: FOGA
Most runtime analyses of randomised search heuristics focus on the expected number of function evaluations to find a unique global optimum. We ask a fundamental question: if additional search points are declared optimal, or declared as desirable targ
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::fd8bb8627905d4660c73739165b079a7
https://doi.org/10.1145/3450218.3477309
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10
On the potential of normalized TSP features for automated algorithm selection
Autor: Heike Trautmann, Pascal Kerschke, Jonathan Heins, Jakob Bossek, Janina Pohl, Moritz Seiler
Publikováno v: FOGA
Classic automated algorithm selection (AS) for (combinatorial) optimization problems heavily relies on so-called instance features, i.e., numerical characteristics of the problem at hand ideally extracted with computationally low-demanding routines.
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3947b36f0617a264ff6b19211ee8a98b
https://doi.org/10.1145/3450218.3477308
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