Quoc Phong Nguyen

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 26

Top Topics

Inverse Reinforcement Learning

Nash Equilibria

Machine Learning

Markov Chain Monte Carlo

Top Venues

Publications

Quoc Phong Nguyen, Wan Theng Ruth Chew, Le Song, Bryan Kian Hsiang Low, Patrick Jaillet
Optimistic Bayesian Optimization with Unknown Constraints. ICLR (2024)
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
Meta-VBO: Utilizing Prior Tasks in Optimizing Risk Measures with Gaussian Processes. ICLR (2024)
Zhongxiang Dai, Quoc Phong Nguyen, Sebastian Tay, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low, Patrick Jaillet
Batch Bayesian Optimization For Replicable Experimental Design. NeurIPS (2023)
Zhongxiang Dai, Quoc Phong Nguyen, Sebastian Shenghong Tay, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low, Patrick Jaillet
Batch Bayesian Optimization for Replicable Experimental Design. CoRR (2023)
Sebastian Shenghong Tay, Quoc Phong Nguyen, Chuan Sheng Foo, Bryan Kian Hsiang Low
No-regret Sample-efficient Bayesian Optimization for Finding Nash Equilibria with Unknown Utilities. AISTATS (2023)
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
Trade-off between Payoff and Model Rewards in Shapley-Fair Collaborative Machine Learning. NeurIPS (2022)
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
Rectified Max-Value Entropy Search for Bayesian Optimization. CoRR (2022)
Quoc Phong Nguyen, Ryutaro Oikawa, Dinil Mon Divakaran, Mun Choon Chan, Bryan Kian Hsiang Low
Markov Chain Monte Carlo-Based Machine Unlearning: Unlearning What Needs to be Forgotten. AsiaCCS (2022)
Quoc Phong Nguyen, Ryutaro Oikawa, Dinil Mon Divakaran, Mun Choon Chan, Bryan Kian Hsiang Low
Markov Chain Monte Carlo-Based Machine Unlearning: Unlearning What Needs to be Forgotten. CoRR (2022)
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
Learning to learn with Gaussian processes. UAI (2021)
Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
Value-at-Risk Optimization with Gaussian Processes. ICML (2021)
Quoc Phong Nguyen, Sebastian Tay, Bryan Kian Hsiang Low, Patrick Jaillet
Top-k Ranking Bayesian Optimization. AAAI (2021)
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
An Information-Theoretic Framework for Unifying Active Learning Problems. AAAI (2021)
Quoc Phong Nguyen, Zhaoxuan Wu, Bryan Kian Hsiang Low, Patrick Jaillet
Trusted-maximizers entropy search for efficient Bayesian optimization. UAI (2021)
Quoc Phong Nguyen, Zhaoxuan Wu, Bryan Kian Hsiang Low, Patrick Jaillet
Trusted-Maximizers Entropy Search for Efficient Bayesian Optimization. CoRR (2021)
Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
Value-at-Risk Optimization with Gaussian Processes. CoRR (2021)
Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
Optimizing Conditional Value-At-Risk of Black-Box Functions. NeurIPS (2021)
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
An Information-Theoretic Framework for Unifying Active Learning Problems. CoRR (2020)
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
Variational Bayesian Unlearning. NeurIPS (2020)
Sreejith Balakrishnan, Quoc Phong Nguyen, Bryan Kian Hsiang Low, Harold Soh
Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization. CoRR (2020)
Sreejith Balakrishnan, Quoc Phong Nguyen, Bryan Kian Hsiang Low, Harold Soh
Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization. NeurIPS (2020)
Quoc Phong Nguyen, Sebastian Tay, Bryan Kian Hsiang Low, Patrick Jaillet
Top-k Ranking Bayesian Optimization. CoRR (2020)
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
Variational Bayesian Unlearning. CoRR (2020)
Quoc Phong Nguyen, Kar Wai Lim, Dinil Mon Divakaran, Kian Hsiang Low, Mun Choon Chan
GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection. CoRR (2019)
Quoc Phong Nguyen, Kar Wai Lim, Dinil Mon Divakaran, Kian Hsiang Low, Mun Choon Chan
GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection. CNS (2019)
Tien Mai, Quoc Phong Nguyen, Kian Hsiang Low, Patrick Jaillet
Inverse Reinforcement Learning with Missing Data. CoRR (2019)
Quoc Phong Nguyen, Kian Hsiang Low, Patrick Jaillet
Inverse Reinforcement Learning with Locally Consistent Reward Functions. NIPS (2015)