Mar 1, 2016 · We present a novel algorithm that provides a rigorous mathematical treatment of the uncertainties arising from model discrepancies and noisy ...

We consider Bayesian methods for multi-information source optimization (MISO), in which we seek to optimize an expensive-to-evaluate black-box objective ...

We consider Bayesian methods for multi-information source optimization (MISO), in which we seek to optimize an expensive-to-evaluate black-box objective ...

We consider Bayesian methods for multi-information source optimization (MISO), in which we seek to optimize an expensive-to-evaluate black-box objective ...

In multi-information source optimization (MISO) the task is to optimize an expensive-to-evaluate black-box objective function while optionally accessing ...

In this study, we optimized a cell culture media with 14 components using a multi-information source Bayesian optimization algorithm that locates optimal media ...

Feb 9, 2021 · This paper addresses black-box optimization over multiple information sources whose both fidelity and query cost change over the search space, that is they are ...

Our proposed multi-information source Bayesian optimization approach for multi-objective optimization using Gaussian processes as the surrogate models and ...

This work presents a novel algorithm that provides a rigorous mathematical treatment of the uncertainties arising from model discrepancies and noisy ...

Optimization of complex systems often involves evaluation of a quantity several times, which is potentially computationally prohibitive.