Estimation of distribution algorithms in machine learning: a survey

P Larrañaga, C Bielza - IEEE Transactions on Evolutionary …, 2023 - ieeexplore.ieee.org
The automatic induction of machine learning models capable of addressing supervised
learning, feature selection, clustering and reinforcement learning problems requires …

Cyberattacks Against Critical Infrastructure Facilities and Corresponding Countermeasures

P Vähäkainu, M Lehto, A Kariluoto - Cyber Security: Critical Infrastructure …, 2022 - Springer
Critical infrastructure (CI) is a vital asset for the economy and society's functioning, covering
sectors such as energy, finance, healthcare, transport, and water supply. Governments …

Gray-box optimization and factorized distribution algorithms: where two worlds collide

R Santana - arXiv preprint arXiv:1707.03093, 2017 - arxiv.org
The concept of gray-box optimization, in juxtaposition to black-box optimization, revolves
about the idea of exploiting the problem structure to implement more efficient evolutionary …

Multi-objective combinatorial generative adversarial optimization and its application in crowdsensing

Y Guo, J Ji, Y Tan, S Cheng - … , ICSI 2020, Belgrade, Serbia, July 14–20 …, 2020 - Springer
With the increasing of the decision variables in multi-objective combinatorial optimization
problems, the traditional evolutionary algorithms perform worse due to the low efficiency for …

Envisioning the benefits of back-drive in evolutionary algorithms

U Garciarena, A Mendiburu… - 2020 IEEE Congress on …, 2020 - ieeexplore.ieee.org
Among the characteristics of traditional evolutionary algorithms governed by models,
memory volatility is one of the most frequent. This is commonly due to the limitations of the …