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An Adaptive Dimension Reduction Estimation Method for High-dimensional Bayesian Optimization
Initially, we identify the effective dimension reduction (EDR) subspace for the objective function using the minimum average variance estimation (MAVE) method.
Adjusted Expected Improvement for Cumulative Regret Minimization in Noisy Bayesian Optimization
To adapt the EI for better performance under cumulative regret, we introduce a novel quantity called the evaluation cost which is compared against the acquisition function, and with this, develop the expected improvement-cost (EIC) algorithm.
Infinite Arms Bandit: Optimality via Confidence Bounds
We present here a confidence bound target (CBT) algorithm that achieves optimality for rewards that are bounded above.
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