Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation

@inproceedings{Bogunovic2016TruncatedVR,
  title={Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation},
  author={Ilija Bogunovic and Jonathan Scarlett and Andreas Krause and Volkan Cevher},
  booktitle={NIPS},
  year={2016}
}
We present a new algorithm, truncated variance reduction (TRUVAR), that treats Bayesian optimization (BO) and level-set estimation (LSE) with Gaussian processes in a unified fashion. The algorithm greedily shrinks a sum of truncated variances within a set of potential maximizers (BO) or unclassified points (LSE), which is updated based on confidence bounds. TRUVAR is effective in several important settings that are typically non-trivial to incorporate into myopic algorithms, including pointwise… CONTINUE READING