Quoc Phong Nguyen

32 papers A* 12A 5Journal 13Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	BILBO: BILevel Bayesian Optimization. ICML Wan Theng Ruth Chew, Quoc Phong Nguyen, Bryan Kian Hsiang Low
2025	J	`jnl`	BILBO: BILevel Bayesian Optimization. CoRR Wan Theng Ruth Chew, Quoc Phong Nguyen, Bryan Kian Hsiang Low
2025	A	`conf`	DUPRE: Data Utility Prediction for Efficient Data Valuation. AAMAS Kieu Thao Nguyen Pham, Rachael Hwee Ling Sim, Quoc Phong Nguyen, See-Kiong Ng, Bryan Kian Hsiang Low
2025	J	`jnl`	DUPRE: Data Utility Prediction for Efficient Data Valuation. CoRR Kieu Thao Nguyen Pham, Rachael Hwee Ling Sim, Quoc Phong Nguyen, See-Kiong Ng, Bryan Kian Hsiang Low
2024	A*	`conf`	Active Set Ordering. NeurIPS Quoc Phong Nguyen, Sunil Gupta, Svetha Venkatesh, Bryan Kian Hsiang Low, Patrick Jaillet
2024	A*	`conf`	Meta-VBO: Utilizing Prior Tasks in Optimizing Risk Measures with Gaussian Processes. ICLR Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
2024	A*	`conf`	Optimistic Bayesian Optimization with Unknown Constraints. ICLR Quoc Phong Nguyen, Wan Theng Ruth Chew, Le Song, Bryan Kian Hsiang Low, Patrick Jaillet
2023	A*	`conf`	Batch Bayesian Optimization For Replicable Experimental Design. NeurIPS Zhongxiang Dai, Quoc Phong Nguyen, Sebastian Tay, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low, Patrick Jaillet
2023	J	`jnl`	Batch Bayesian Optimization for Replicable Experimental Design. CoRR Zhongxiang Dai, Quoc Phong Nguyen, Sebastian Shenghong Tay, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low, Patrick Jaillet
2023	A	`conf`	No-regret Sample-efficient Bayesian Optimization for Finding Nash Equilibria with Unknown Utilities. AISTATS Sebastian Shenghong Tay, Quoc Phong Nguyen, Chuan Sheng Foo, Bryan Kian Hsiang Low
2022	A	`conf`	Markov Chain Monte Carlo-Based Machine Unlearning: Unlearning What Needs to be Forgotten. AsiaCCS Quoc Phong Nguyen, Ryutaro Oikawa, Dinil Mon Divakaran, Mun Choon Chan, Bryan Kian Hsiang Low
2022	J	`jnl`	Markov Chain Monte Carlo-Based Machine Unlearning: Unlearning What Needs to be Forgotten. CoRR Quoc Phong Nguyen, Ryutaro Oikawa, Dinil Mon Divakaran, Mun Choon Chan, Bryan Kian Hsiang Low
2022	J	`jnl`	Rectified Max-Value Entropy Search for Bayesian Optimization. CoRR Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
2022	A*	`conf`	Trade-off between Payoff and Model Rewards in Shapley-Fair Collaborative Machine Learning. NeurIPS Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
2021	A*	`conf`	An Information-Theoretic Framework for Unifying Active Learning Problems. AAAI Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
2021	A	`conf`	Learning to learn with Gaussian processes. UAI Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
2021	A*	`conf`	Optimizing Conditional Value-At-Risk of Black-Box Functions. NeurIPS Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
2021	A*	`conf`	Top-k Ranking Bayesian Optimization. AAAI Quoc Phong Nguyen, Sebastian Tay, Bryan Kian Hsiang Low, Patrick Jaillet
2021	J	`jnl`	Trusted-Maximizers Entropy Search for Efficient Bayesian Optimization. CoRR Quoc Phong Nguyen, Zhaoxuan Wu, Bryan Kian Hsiang Low, Patrick Jaillet
2021	A	`conf`	Trusted-maximizers entropy search for efficient Bayesian optimization. UAI Quoc Phong Nguyen, Zhaoxuan Wu, Bryan Kian Hsiang Low, Patrick Jaillet
2021	A*	`conf`	Value-at-Risk Optimization with Gaussian Processes. ICML Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
2021	J	`jnl`	Value-at-Risk Optimization with Gaussian Processes. CoRR Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
2020	J	`jnl`	An Information-Theoretic Framework for Unifying Active Learning Problems. CoRR Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
2020	A*	`conf`	Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization. NeurIPS Sreejith Balakrishnan, Quoc Phong Nguyen, Bryan Kian Hsiang Low, Harold Soh
2020	J	`jnl`	Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization. CoRR Sreejith Balakrishnan, Quoc Phong Nguyen, Bryan Kian Hsiang Low, Harold Soh
2020	J	`jnl`	Top-k Ranking Bayesian Optimization. CoRR Quoc Phong Nguyen, Sebastian Tay, Bryan Kian Hsiang Low, Patrick Jaillet
2020	A*	`conf`	Variational Bayesian Unlearning. NeurIPS Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
2020	J	`jnl`	Variational Bayesian Unlearning. CoRR Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
2019	—	`conf`	GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection. CNS Quoc Phong Nguyen, Kar Wai Lim, Dinil Mon Divakaran, Kian Hsiang Low, Mun Choon Chan
2019	J	`jnl`	GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection. CoRR Quoc Phong Nguyen, Kar Wai Lim, Dinil Mon Divakaran, Kian Hsiang Low, Mun Choon Chan
2019	J	`jnl`	Inverse Reinforcement Learning with Missing Data. CoRR Tien Mai, Quoc Phong Nguyen, Kian Hsiang Low, Patrick Jaillet
2015	—	`conf`	Inverse Reinforcement Learning with Locally Consistent Reward Functions. NIPS Quoc Phong Nguyen, Kian Hsiang Low, Patrick Jaillet