Abstract: Interaction design typically involves challenging decision making that requires designers to consider multiple parameters and careful tradeoffs between various objectives. This article ...

As the default choice for surrogate modeling in multi-objective Bayesian optimization (MOBO), Gaussian processes (GPs) struggle with irregular high-dimensional variables and non-stationary spaces. To ...

SAIBO stands for Scientific Artificial Intelligence Bayesian Optimization. SAIBO is a research framework for bringing scientific reasoning agents into Bayesian optimization loops. It is designed for ...

With the high penetration of renewable energy, electricity spot market prices exhibit significant temporal volatility, exposing photovoltaic (PV) power plants to the risk of “price cannibalization” ...

Here, we benchmark five global optimization methods for three typical nano-optical optimization problems: particle swarm optimization, differential evolution, and Bayesian optimization as well as ...

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CATO leverages recent advances in multi-objective Bayesian optimization to efficiently identify Pareto-optimal configurations, and automatically compiles end-to-end optimized serving pipelines that ...