Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Roland Olsson"'
Publikováno v:
IEEE Open Journal of the Industrial Electronics Society, Vol 5, Pp 91-108 (2024)
Analyzing time series data in industrial settings demands domain knowledge and computer science expertise to develop effective algorithms. AutoML approaches aim to automate this process, reducing human bias and improving accuracy and cost-effectivene
Externí odkaz:
https://doaj.org/article/54dc882de70b4b6b9d2af31b0fb21b09
Publikováno v:
IEEE Intelligent Systems. 38:73-80
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::69acccd5c3a4973d72e11cb51acaec63
https://doi.org/10.1109/mis.2023.3252446
https://doi.org/10.1109/mis.2023.3252446
Autor:
Roland Olsson, Shubodha Acharya
Publikováno v:
Artificial Intelligence and Soft Computing ISBN: 9783031234910
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3dc7cb70b81963b429b8de6b182303f0
https://doi.org/10.1007/978-3-031-23492-7_21
https://doi.org/10.1007/978-3-031-23492-7_21
Autor:
Marius Geitle, Roland Olsson
Publikováno v:
Machine Learning, Optimization, and Data Science ISBN: 9783030375980
LOD
LOD
Finding the optimal hyper-parameters values for a given problem is essential for most machine learning algorithms. In this paper, we propose a novel hyper-parameter optimization algorithm that is very simple to implement and still competitive with th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a19f0d0a6b52309069eaa748bb19de24
https://doi.org/10.1007/978-3-030-37599-7_43
https://doi.org/10.1007/978-3-030-37599-7_43
Autor:
Marius Geitle, Roland Olsson
Publikováno v:
ICSAI
In this paper, we automatically improve the competitive differential evolution algorithm through automatic programming. The improved algorithm outperforms the original for over 73% of the 50-dimensional CEC 2014 problems and is worse for less than 17
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::52babe537fd14406a4353b9e2a96cb39
https://doi.org/10.1109/icsai.2017.8248350
https://doi.org/10.1109/icsai.2017.8248350
Autor:
Roland Olsson, Marius Geitle
Publikováno v:
2017 21st Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES).
To automatically design improvements of stochastic numerical optimization algorithms is challenging due to the high computation time required to ensure sufficiently rigorous evaluation of synthesized programs. In this paper, we develop evaluation met
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5b1debd3b175570f9e4d8ef5460b6bd
https://doi.org/10.1109/iesys.2017.8233554
https://doi.org/10.1109/iesys.2017.8233554
Publikováno v:
BigComp
With the emergence of cloud computing and sensor technologies, Big Data analytics for the Internet of Things (IoT) has become the main force behind many innovative solutions for our society's problems. This paper provides practical explanations for t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9128fb7b0d9eda8a928c64d31344db43
http://arxiv.org/abs/1703.02510
http://arxiv.org/abs/1703.02510
Publikováno v:
IJCNN
Short-Term Load Forecasting (STLF) is a fundamental component in the efficient management of power systems, which has been studied intensively over the past 50 years. The emerging development of smart grid technologies is posing new challenges as wel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::42f048410f8d02a3e9f7e3a413743311
Autor:
Arne Løkketangen, Roland Olsson
Publikováno v:
Journal of Heuristics. 19:819-844
The paper focuses on automatic programming and how to synthesize stochastic local search algorithms using automatic design of algorithms through evolution (ADATE). The main goal is to provide support for the hypothesis that automatic programming can
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::323377400af4c10cf81d738a38ce5210
https://doi.org/10.1007/s10732-013-9226-x
https://doi.org/10.1007/s10732-013-9226-x
Autor:
Lars Vidar Magnusson, Roland Olsson
Publikováno v:
2016 International Conference on Image, Vision and Computing (ICIVC).
We have used automatic programming, a machine learning technique related to inductive logic programming and genetic programming, to make the Canny edge detector better at identifying contours in natural images. We present an improved version of the f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2930a78e7332cacd6cfc85ef73fea0b8
https://doi.org/10.1109/icivc.2016.7571270
https://doi.org/10.1109/icivc.2016.7571270