32 citations · 45 across the 7 of their papers we have counts for
8 papers
Trusted-Maximizers Entropy Search for Efficient Bayesian Optimization
Quoc Phong Nguyen, Zhaoxuan Wu, Bryan Kian Hsiang Low +1
Information-based Bayesian optimization (BO) algorithms have achieved state-of-the-art performance in optimizing a black-box objective function. However, they usually require sever…
Value-at-Risk Optimization with Gaussian Processes
Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low +1
Value-at-risk (VaR) is an established measure to assess risks in critical real-world applications with random environmental factors. This paper presents a novel VaR upper confidenc…
An Information-Theoretic Framework for Unifying Active Learning Problems
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
This paper presents an information-theoretic framework for unifying active learning problems: level set estimation (LSE), Bayesian optimization (BO), and their generalized variant.…
Top- Ranking Bayesian Optimization
Quoc Phong Nguyen, Sebastian Tay, Bryan Kian Hsiang Low +1
This paper presents a novel approach to top- ranking Bayesian optimization (top- ranking BO) which is a practical and significant generalization of preferential BO to handle…
Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization
Sreejith Balakrishnan, Quoc Phong Nguyen, Bryan Kian Hsiang Low +1
The problem of inverse reinforcement learning (IRL) is relevant to a variety of tasks including value alignment and robot learning from demonstration. Despite significant algorithm…
Variational Bayesian Unlearning
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
This paper studies the problem of approximately unlearning a Bayesian model from a small subset of the training data to be erased. We frame this problem as one of minimizing the Ku…