2 citations · 2 across the 3 of their papers we have counts for
3 papers
Bayesian Preference Elicitation: Human-In-The-Loop Optimization of An Active Prosthesis
Sophia Taddei, Wouter Koppen, Eligia Alfio +8
Tuning active prostheses for people with amputation is time-consuming and relies on metrics that may not fully reflect user needs. We introduce a human-in-the-loop optimization (HI…
Bayesian preference elicitation for decision support in multiobjective optimization
Felix Huber, Sebastian Rojas Gonzalez, Raul Astudillo
We present a novel approach to help decision-makers efficiently identify preferred solutions from the Pareto set of a multi-objective optimization problem. Our method uses a Bayesi…
A survey on multi-objective hyperparameter optimization algorithms for Machine Learning
Alejandro Morales-Hernández, Inneke Van Nieuwenhuyse, Sebastian Rojas Gonzalez
Hyperparameter optimization (HPO) is a necessary step to ensure the best possible performance of Machine Learning (ML) algorithms. Several methods have been developed to perform HP…