Zobrazeno 1 - 10
of 1 159
pro vyhledávání: '"P. Bliek"'
Autor:
Deborah J. G. Mackay, Gabriella Gazdagh, David Monk, Frederic Brioude, Eloise Giabicani, Izabela M. Krzyzewska, Jennifer M. Kalish, Saskia M. Maas, Masayo Kagami, Jasmin Beygo, Tiina Kahre, Jair Tenorio-Castano, Laima Ambrozaitytė, Birutė Burnytė, Flavia Cerrato, Justin H. Davies, Giovanni Battista Ferrero, Olga Fjodorova, Africa Manero-Azua, Arrate Pereda, Silvia Russo, Pierpaola Tannorella, Karen I. Temple, Katrin Õunap, Andrea Riccio, Guiomar Perez de Nanclares, Eamonn R. Maher, Pablo Lapunzina, Irène Netchine, Thomas Eggermann, Jet Bliek, Zeynep Tümer
Publikováno v:
Clinical Epigenetics, Vol 16, Iss 1, Pp 1-19 (2024)
Abstract Background Imprinting disorders are rare diseases resulting from altered expression of imprinted genes, which exhibit parent-of-origin-specific expression patterns regulated through differential DNA methylation. A subgroup of patients with i
Externí odkaz:
https://doaj.org/article/55647b2d116f4168a75d09b18186ddb5
Algorithm selection is a well-known problem where researchers investigate how to construct useful features representing the problem instances and then apply feature-based machine learning models to predict which algorithm works best with the given in
Externí odkaz:
http://arxiv.org/abs/2302.04035
Urban traffic attributed to commercial and industrial transportation is observed to largely affect living standards in cities due to external effects pertaining to pollution and congestion. In order to counter this, smart cities deploy technological
Externí odkaz:
http://arxiv.org/abs/2302.00484
Multi-objective evolutionary algorithms (MOEAs) are widely used to solve multi-objective optimization problems. The algorithms rely on setting appropriate parameters to find good solutions. However, this parameter tuning could be very computationally
Externí odkaz:
http://arxiv.org/abs/2211.09719
Autor:
Teso, Stefano, Bliek, Laurens, Borghesi, Andrea, Lombardi, Michele, Yorke-Smith, Neil, Guns, Tias, Passerini, Andrea
It is increasingly common to solve combinatorial optimisation problems that are partially-specified. We survey the case where the objective function or the relations between variables are not known or are only partially specified. The challenge is to
Externí odkaz:
http://arxiv.org/abs/2205.10157
Autor:
Bliek, Laurens, da Costa, Paulo, Afshar, Reza Refaei, Zhang, Yingqian, Catshoek, Tom, Vos, Daniël, Verwer, Sicco, Schmitt-Ulms, Fynn, Hottung, André, Shah, Tapan, Sellmann, Meinolf, Tierney, Kevin, Perreault-Lafleur, Carl, Leboeuf, Caroline, Bobbio, Federico, Pepin, Justine, Silva, Warley Almeida, Gama, Ricardo, Fernandes, Hugo L., Zaefferer, Martin, López-Ibáñez, Manuel, Irurozki, Ekhine
This paper reports on the first international competition on AI for the traveling salesman problem (TSP) at the International Joint Conference on Artificial Intelligence 2021 (IJCAI-21). The TSP is one of the classical combinatorial optimization prob
Externí odkaz:
http://arxiv.org/abs/2201.10453
Publikováno v:
Frontiers in Neuroergonomics, Vol 5 (2024)
Externí odkaz:
https://doaj.org/article/79f964ce20ee4c18bf81f5a42182ffd0
Surrogate algorithms such as Bayesian optimisation are especially designed for black-box optimisation problems with expensive objectives, such as hyperparameter tuning or simulation-based optimisation. In the literature, these algorithms are usually
Externí odkaz:
http://arxiv.org/abs/2106.04618
Review of Rob van der Bliek, ed. 2001. The Thelonious Monk Reader. New York: Oxford University Press
Autor:
Brian Priestley
Publikováno v:
Current Musicology, Iss 71-73 (2001)
The music of Thelonious Monk has evoked increasing interest in the twenty years since his death. His themes, which used to be thought unappetizing for others to play, are now eagerly lapped up by performance students, as well as by those professional
Externí odkaz:
https://doaj.org/article/b57d03ca78cd4515b1a2ad716355825c
Publikováno v:
Proceedings of BNAIC/BeneLearn (2020), 88-102
One method to solve expensive black-box optimization problems is to use a surrogate model that approximates the objective based on previous observed evaluations. The surrogate, which is cheaper to evaluate, is optimized instead to find an approximate
Externí odkaz:
http://arxiv.org/abs/2011.03431