In today's scientific and industrial fields, high-dimensional data in which numerous variables are observed simultaneously, such as genomic, climate, financial, and sensor data, are rapidly increasing ...
This repository contains the code to run the experiments in the paper (Buckingham et al., 2025): Buckingham, J. M., Rojas Gonzalez, S., & Branke, J. (2025). Knowledge Gradient for Multi-Objective ...
Abstract: Automated Class Imbalance Learning (AutoCIL) is an emerging paradigm that leverages Combined Algorithm Selection and Hyperparameter Optimization (CASH) to automate the configuration of ...
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Abstract: Duringthe design of electrical machines, multiple performance objectives need to be considered. Although stochastic optimization algorithms are extensively employed for this purpose, a ...
Sediment plumes created by dredging or mining activities have an impact on the ecosystem in a much larger area than the mining or dredging area itself. It is therefore important and sometimes ...
CDM-PSL (Composite Diffusion Model-Based Pareto Set Learning) is a novel algorithm designed to address the challenges of expensive multi-objective Bayesian optimization (EMOBO). While MOBO has shown ...