Scholar
Quoc Phong Nguyen
Google Scholar ID: QesBBHYAAAAJ
A2I2 - Deakin University
Citations & Impact
Citations
701
H-index
11
i10-index
11
Publications
20
Co-authors
0
Contact
Publications
Resume (English only)
Academic Achievements
- Publications:
- - "Optimizing Conditional Value-At-Risk of Black-Box Functions" at NeurIPS 2021
- - "Value-at-Risk Optimization with Gaussian Processes" at ICML 2021
- - "Top-k Ranking Bayesian Optimization" at AAAI 2021
- - "Rectified Max-Value Entropy Search for Bayesian Optimization" on arXiv 2022
- - "An Information-Theoretic Framework for Unifying Active Learning Problems" at AAAI 2021
- - "Trusted-Maximizers Entropy Search for Efficient Bayesian Optimization" at UAI 2021
- - "No-Regret Sample-Efficient Bayesian Optimization for Finding Nash Equilibria with Unknown Utilities" at AISTATS 2023
- - "Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization" at NeurIPS 2020
- - Work on active inverse reinforcement learning at the Workshop at NeurIPS 2017
- Recent Achievements:
- - Work on active set ordering accepted for poster presentation at NeurIPS 2024
- - Meta Bayesian optimization and constrained Bayesian optimization accepted for poster presentation at ICLR 2024
Research Experience
- Currently a Research Fellow at Deakin University, working with Professor Sunil Gupta and Professor Svetha Venkatesh; presented research on optimizing Value-at-risk and Conditional Value-at-risk of black-box functions at the 2023 INFORMS Annual Meeting.
Education
- PhD in Machine Learning from the National University of Singapore (NUS), under the guidance of Professor Bryan Kian Hsiang Low and Professor Patrick Jaillet
Background
- Research Interests: Bayesian optimization, active learning, meta-learning, fairness in collaborative machine learning, machine unlearning, explainable AI, and inverse reinforcement learning. Currently focusing on devising a general approach that unifies several problems related to Bayesian optimization.
Co-authors