About Me
Hello! I am Guanghui Wang (王广辉), a fourth-year PhD student in Machine Learning at Georgia Institute of Technology. I am very fortunate to be advised by Prof. Jake Abernethy and Prof. Vidya Muthukumar.
Before joining Georgia Tech, I obtained my M.S. degree from Department of Computer Science and Technology in Nanjing University in 2020, where I was very fortunate to be advised by Prof. Lijun Zhang. I was also a member of the LAMDA group, led by Prof. Zhi-Hua Zhou. I received my B.E. degree from School of Electronic Engineering in Xidian University in 2017.
I am interested in online learning, stochastic optimization, and game theory.
Publications
Preprints
Conference Papers
- Faster Margin Maximization Rates for Generic Optimization Methods
Guanghui Wang, Zihao Hu, Vidya Muthukumar, Jacob Abernethy.
NeurIPS 2023 (Spotlight).
- On Riemannian Projection-free Online Learning
Zihao Hu, Guanghui Wang, Jacob Abernethy.
NeurIPS 2023.
- Minimizing Dynamic Regret on Geodesic Metric Spaces
Zihao Hu, Guanghui Wang, Jacob Abernethy.
COLT2023. To appear.
- On Accelerated Perceptrons and Beyond
Guanghui Wang, Rafael Hanashiro, Etash Guha, Jacob Abernethy.
ICLR 2023.
- Adaptive Oracle-Efficient Online Learning
Guanghui Wang, Zihao Hu, Vidya Muthukumar, Jacob Abernethy.
NeurIPS 2022.
- A Simple yet Universal Strategy for Online Convex Optimization
Lijun Zhang, Guanghui Wang, Jinfeng Yi, Tianbao Yang.
ICML 2022.
- Momentum Accelerates the Convergence of Stochastic AUPRC Maximization
Guanghui Wang, Ming Yang, Lijun Zhang, Tianbao Yang.
AISTATS 2022.
- Online Convex Optimization with Continuous Switching Constraint
Guanghui Wang, Yuanyu Wan, Tianbao Yang, Lijun Zhang
NeurIPS 2021.
- Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions
Lijun Zhang, Guanghui Wang, Wei-Wei Tu, Wei Jiang, Zhi-Hua Zhou.
NeurIPS 2021.
- Stochastic Graphical Bandits with Adversarial Corruptions
Shiyin Lu, Guanghui Wang, Lijun Zhang.
AAAI 2021.
- Sadam: A Variant of Adam for Strongly Convex Functions
Guanghui Wang, Shiyin Lu, Quan Cheng, Wei-Wei Tu, Lijun Zhang.
ICLR 2020.
- Bandit Convex Optimization in Non-stationary Environments.
Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou.
AISTATS 2020.
- Adapting to Smoothness: A More Universal Algorithm for Online Convex Optimization
Guanghui Wang, Shiyin Lu, Yao Hu, Lijun Zhang.
AAAI 2020.
- Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs
Bo Xue, Guanghui Wang, Yimu Wang, Lijun Zhang.
IJCAI 2020.
- Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization
Guanghui Wang, Shiyin Lu, Lijun Zhang.
UAI 2019.
- Multi-Objective Generalized Linear Bandits
Shiyin Lu, Guanghui Wang, Yao Hu, Lijun Zhang.
IJCAI 2019.
- Optimal Algorithms for Lipschitz Bandits with Heavy-Tailed Rewards
Shiyin Lu, Guanghui Wang, Yao Hu, Lijun Zhang.
ICML 2019.
- Minimizing Adaptive Regret with One Gradient per Iteration
Guanghui Wang, Dakuan Zhao, Lijun Zhang.
IJCAI 2018.
Journal Articles
- Projection-free Distributed Online Learning with Sublinear Communication Complexity
Yuanyu Wan, Guanghui Wang, Wei-Wei Tu, Lijun Zhang.
JMLR 2022.
- Bandit Convex Optimization in Non-stationary Environments
Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou.
JMLR 2021.
Academic Service
Reviewer: ICML, ICLR, NeurIPS, AISTATS, TMLR
Teaching
- TA, ECE 8803 Online Decision Making in Machine Learning, Fall 2021
- TA, co-instructor (6 lectures), ECE 8803 Online Decision Making in Machine Learning, Fall 2022
- TA, co-instructor (6 lectures), CS7545 Machine Learning Theory, Spring 2023
- co-instructor (2 lectures), ECE 8803 Online Decision Making in Machine Learning, Fall 2023
Working\Visiting Experience
- Visiting Graduate Student, Spring 2021, Simons Institute for the Theory of Computing.
- Reseach Assistant, Fall 2020 - Fall 2021, Nanjing University.
Awards
- ARC-ACO Fellowship, 2022.
- National Scholarship, 2014, 2018.