The investigation of mixture models is a key to understand and visualize...
Quantization summarizes continuous distributions by calculating a discre...
Visualization is an essential operation when assessing the risk of rare
...
Most real optimization problems are defined over a mixed search space wh...
It is commonly believed that Bayesian optimization (BO) algorithms are h...
We consider the problem of chance constrained optimization where it is s...
Efficient Global Optimization (EGO) is the canonical form of Bayesian
op...
Parametric shape optimization aims at minimizing an objective function f...
At the initial design stage engineers often rely on low-fidelity models ...
The optimization of high dimensional functions is a key issue in enginee...
Multi-objective optimization aims at finding trade-off solutions to
conf...
Optimizing nonlinear systems involving expensive (computer) experiments ...
The Efficient Global Optimization (EGO) algorithm uses a conditional
Gau...
Gaussian Processes (GPs) are a popular approach to predict the output of...