Research map / Probabilistic and scientific modeling / Bayesian optimization
Multi-fidelity Bayesian Optimisation with Continuous Approximations
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use BOCA to exploit information from continuous fidelities instead of optimizing only at the target fidelity | Bayesian optimization with continuous approximations · Synthetic problems | simple regret | Helped |
| Use BOCA rather than MF-GP-UCB or MF-SKO | Bayesian optimization with continuous approximations · Borehole function | simple regret | Hurt |
| Use BOCA rather than finite-fidelity baselines | Bayesian optimization with continuous approximations · Branin function | simple regret | Helped |
| Use BOCA with a smooth fidelity dimension | Bayesian optimization with continuous approximations · Synthetic GP, fidelity bandwidth 1.0 | simple regret | Helped |
| Use BOCA with an unsmooth fidelity dimension | Bayesian optimization with continuous approximations · Synthetic GP, fidelity bandwidth 0.01 | simple regret | No clear effect |
| Use BOCA rather than the compared baselines | Bayesian optimization with continuous approximations · Type Ia supernova likelihood optimization | maximum average log likelihood | Mixed |
| Use BOCA rather than the compared baselines | Bayesian optimization with continuous approximations · 20 Newsgroups classification | cross-validation accuracy | Mixed |
| Exploit lower-fidelity observations through the continuous-fidelity GP model | BOCA · Theoretical simple-regret analysis | simple regret | Helped |
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