Zhenjie Lu

CAMO: Convergence-Aware Multi-Fidelity Bayesian Optimization

CAMO (Convergence-Aware Multi-fidelity Optimization), a principled framework based on Linear Fidelity Differential Equations that explicitly encodes convergence of fidelity-indexed outputs and employs a closed-form nonstationary kernel, is introduced.