most citedBayesian Optimization with Unknown Search Space

25 citations · 38 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ML20205 cited

Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling

Cheng Li, Sunil Gupta, Santu Rana +3

Scientific experiments are usually expensive due to complex experimental preparation and processing. Experimental design is therefore involved with the task of finding the optimal…

cs.LG20206 cited

Distributionally Robust Bayesian Quadrature Optimization

Thanh Tang Nguyen, Sunil Gupta, Huong Ha +2

Bayesian quadrature optimization (BQO) maximizes the expectation of an expensive black-box integrand taken over a known probability distribution. In this work, we study BQO under d…

cs.LG20192 cited

Bayesian Optimization for Categorical and Category-Specific Continuous Inputs

Dang Nguyen, Sunil Gupta, Santu Rana +2

Many real-world functions are defined over both categorical and category-specific continuous variables and thus cannot be optimized by traditional Bayesian optimization (BO) method…

stat.ML201925 cited

Bayesian Optimization with Unknown Search Space

Huong Ha, Santu Rana, Sunil Gupta +3

Applying Bayesian optimization in problems wherein the search space is unknown is challenging. To address this problem, we propose a systematic volume expansion strategy for the Ba…

stat.ML2019

Stable Bayesian Optimisation via Direct Stability Quantification

Alistair Shilton, Sunil Gupta, Santu Rana +3

In this paper we consider the problem of finding stable maxima of expensive (to evaluate) functions. We are motivated by the optimisation of physical and industrial processes where…