activity
20192021
most citedBayesian Optimization with Unknown Search Space

25 citations · 32 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2021

ALT-MAS: A Data-Efficient Framework for Active Testing of Machine Learning Algorithms

Huong Ha, Sunil Gupta, Santu Rana +1

Machine learning models are being used extensively in many important areas, but there is no guarantee a model will always perform well or as its developers intended. Understanding…

stat.ML2021

Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces

Xingchen Wan, Vu Nguyen, Huong Ha +3

High-dimensional black-box optimisation remains an important yet notoriously challenging problem. Despite the success of Bayesian optimisation methods on continuous domains, domain…

stat.ML20201 cited

High Dimensional Level Set Estimation with Bayesian Neural Network

Huong Ha, Sunil Gupta, Santu Rana +1

Level Set Estimation (LSE) is an important problem with applications in various fields such as material design, biotechnology, machine operational testing, etc. Existing techniques…

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…

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…