4 citations · 6 across the 2 of their papers we have counts for
4 papers
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…