3 citations · 7 across the 4 of their papers we have counts for
4 papers
To Switch or not to Switch: Predicting the Benefit of Switching between Algorithms based on Trajectory Features
Diederick Vermetten, Hao Wang, Kevin Sim +1
Dynamic algorithm selection aims to exploit the complementarity of multiple optimization algorithms by switching between them during the search. While these kinds of dynamic algori…
High Dimensional Bayesian Optimization with Kernel Principal Component Analysis
Kirill Antonov, Elena Raponi, Hao Wang +1
Bayesian Optimization (BO) is a surrogate-based global optimization strategy that relies on a Gaussian Process regression (GPR) model to approximate the objective function and an a…
Per-run Algorithm Selection with Warm-starting using Trajectory-based Features
Ana Kostovska, Anja Jankovic, Diederick Vermetten +4
Per-instance algorithm selection seeks to recommend, for a given problem instance and a given performance criterion, one or several suitable algorithms that are expected to perform…
Squirrel: A Switching Hyperparameter Optimizer
Noor Awad, Gresa Shala, Difan Deng +9
In this short note, we describe our submission to the NeurIPS 2020 BBO challenge. Motivated by the fact that different optimizers work well on different problems, our approach swit…