65 citations · 108 across the 7 of their papers we have counts for
9 papers
LLMDE: A Large Language Model-Driven Differential Evolution Algorithm for Portfolio Optimization
Rong Chai, Vaclav Snasel, Xiaopeng Wang +2
This study proposes a Large Language Model-Driven Differential Evolution (LLMDE) algorithm to reduce the reliance on handcrafted hyperparameter design. The proposed algorithm lever…
Individualised recovery trajectories of patients with impeded mobility, using distance between probability distributions of learnt graphs
Chuqiao Zhang, Crina Grosan, Dalia Chakrabarty
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 p…
Explainable AI: Definition and attributes of a good explanation for health AI
Evangelia Kyrimi, Scott McLachlan, Jared M Wohlgemut +4
Proposals of artificial intelligence (AI) solutions based on increasingly complex and accurate predictive models are becoming ubiquitous across many disciplines. As the complexity…
Using Traceless Genetic Programming for Solving Multiobjective Optimization Problems
Mihai Oltean, Crina Grosan
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 mai…
Evolving Evolutionary Algorithms using Multi Expression Programming
Mihai Oltean, Crina Groşan
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…
Evolving Digital Circuits for the Knapsack Problem
Mihai Oltean, Crina Groşan, Mihaela Oltean
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…
Classifying action correctness in physical rehabilitation exercises
Alina Miron, Crina Grosan
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 an…
Meta-QSAR: a large-scale application of meta-learning to drug design and discovery
Ivan Olier, Noureddin Sadawi, G. Richard Bickerton +4
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,…
A Collection of Challenging Optimization Problems in Science, Engineering and Economics
Dhagash Mehta, Crina Grosan
Function optimization and finding simultaneous solutions of a system of nonlinear equations (SNE) are two closely related and important optimization problems. However, unlike in th…