Zobrazeno 1 - 10
of 69
pro vyhledávání: '"GROŞAN, CRINA"'
Publikováno v:
Artificial Intelligence in Medicine, 2024
Patients who are undergoing physical rehabilitation, benefit from feedback that follows from reliable assessment of their cumulative performance attained at a given time. In this paper, we provide a method for the learning of the recovery trajectory
Externí odkaz:
http://arxiv.org/abs/2410.21983
Autor:
Oltean, Mihai, Grosan, Crina
Publikováno v:
Journal of Experimental and Theoretical Artificial Intelligence, Taylor & Francis, Vol. 19, pp. 227-248, 2007
Traceless Genetic Programming (TGP) is a Genetic Programming (GP) variant that is used in cases where the focus is rather the output of the program than the program itself. The main difference between TGP and other GP techniques is that TGP does not
Externí odkaz:
http://arxiv.org/abs/2110.13608
Autor:
Oltean, Mihai, Groşan, Crina
Publikováno v:
European Conference on Artificial Life, LNCS 2801, pp. 651-658, 2003
Finding the optimal parameter setting (i.e. the optimal population size, the optimal mutation probability, the optimal evolutionary model etc) for an Evolutionary Algorithm (EA) is a difficult task. Instead of evolving only the parameters of the algo
Externí odkaz:
http://arxiv.org/abs/2109.13737
Publikováno v:
E-HARD Workshop, Edited by M. Bubak, G. D. van Albada, P. Sloot, and J. Dongarra, Vol. III, pp. 1257-1264, 6-9 June, Krakow, Poland, Springer-Verlag, Berlin, 2004
Multi Expression Programming (MEP) is a Genetic Programming variant that uses linear chromosomes for solution encoding. A unique feature of MEP is its ability of encoding multiple solutions of a problem in a single chromosome. In this paper we use Mu
Externí odkaz:
http://arxiv.org/abs/2109.13107
Autor:
Miron, Alina, Grosan, Crina
The work in this paper focuses on the role of machine learning in assessing the correctness of a human motion or action. This task proves to be more challenging than the gesture and action recognition ones. We will demonstrate, through a set of exper
Externí odkaz:
http://arxiv.org/abs/2108.01375
Publikováno v:
In Data & Knowledge Engineering January 2023 143
Autor:
Olier, Ivan, Sadawi, Noureddin, Bickerton, G. Richard, Vanschoren, Joaquin, Grosan, Crina, Soldatova, Larisa, King, Ross D.
We investigate the learning of quantitative structure activity relationships (QSARs) as a case-study of meta-learning. This application area is of the highest societal importance, as it is a key step in the development of new medicines. The standard
Externí odkaz:
http://arxiv.org/abs/1709.03854
Publikováno v:
In Artificial Intelligence In Medicine October 2021 120
Autor:
Mehta, Dhagash, Grosan, Crina
Function optimization and finding simultaneous solutions of a system of nonlinear equations (SNE) are two closely related and important optimization problems. However, unlike in the case of function optimization in which one is required to find the g
Externí odkaz:
http://arxiv.org/abs/1504.02366
Autor:
Zawbaa, Hossam M., Schiano, Serena, Perez-Gandarillas, Lucia, Grosan, Crina, Michrafy, A., Wu, Chuan-Yu
Publikováno v:
In Advanced Powder Technology December 2018 29(12):2966-2977