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The Parallel Knowledge Gradient Method for Batch Bayesian Optimization
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use q-KG batch acquisition instead of parallel EI / batch UCB | batch Bayesian optimization · noise-free Rosenbrock3, Ackley5, Hartmann6 (q=4) | immediate regret | Helped |
| use q-KG instead of best baseline | batch Bayesian optimization · noise-free Branin2 (q=4) | immediate regret | Hurt |
| use q-KG instead of parallel EI | hyperparameter tuning · CIFAR10 CNN | test error: around 14% -> around 11% (vs human tuning) | Helped |
| use q-KG instead of parallel EI | hyperparameter tuning · MNIST logistic regression | test error | Helped |
| use q-KG under noisy evaluations | batch Bayesian optimization · noisy synthetic functions (σ=0.5) | immediate regret | Helped |
| use q-KG with small noisy test sets | hyperparameter tuning · MNIST logistic regression, 1000-sample test set | full test error | Helped |
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