activity
20192025
most citedBayesian Optimization with Unknown Search Space

25 citations · 26 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Hybrid Cross-domain Robust Reinforcement Learning

Linh Le Pham Van, Minh Hoang Nguyen, Hung Le +2

Robust reinforcement learning (RL) aims to learn policies that remain effective despite uncertainties in its environment, which frequently arise in real-world applications due to v…

cs.LG2024

High-Dimensional Bayesian Optimization via Random Projection of Manifold Subspaces

Quoc-Anh Hoang Nguyen, The Hung Tran

Bayesian Optimization (BO) is a popular approach to optimizing expensive-to-evaluate black-box functions. Despite the success of BO, its performance may decrease exponentially as t…

cs.LG2024

Bayesian Optimization for Unknown Cost-Varying Variable Subsets with No-Regret Costs

Vu Viet Hoang, Quoc Anh Hoang Nguyen, Hung Tran The

Bayesian Optimization (BO) is a widely-used method for optimizing expensive-to-evaluate black-box functions. Traditional BO assumes that the learner has full control over all query…

stat.ML20211 cited

Combining Online Learning and Offline Learning for Contextual Bandits with Deficient Support

Hung Tran-The, Sunil Gupta, Thanh Nguyen-Tang +2

We address policy learning with logged data in contextual bandits. Current offline-policy learning algorithms are mostly based on inverse propensity score (IPS) weighting requiring…

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…