Preprint
- Conditional Generative Representation for Black-Box Optimization with Implicit Constraints
Wenqian Xing, Jungho Lee, Chong Liu, and Shixiang Zhu.
ArXiv Preprint: 2310.18449. [ArXiv]
Conference
- Communication-Efficient Federated Non-Linear Bandit Optimization
Chuanhao Li *, Chong Liu *, and Yu-Xiang Wang. (* equal contribution)
The 12th International Conference on Learning Representations (ICLR-2024), Vienna, Austria, 2024. [ArXiv]
- No-Regret Linear Bandits beyond Realizability
Chong Liu, Ming Yin, and Yu-Xiang Wang.
The 39th Conference on Uncertainty in Artificial Intelligence (UAI-2023), Pittsburgh, PA, 2023, pp. 1294-1303. [PMLR] [ArXiv]
- Global Optimization with Parametric Function Approximation
Chong Liu and Yu-Xiang Wang.
The 40th International Conference on Machine Learning (ICML-2023), Honolulu, HI, 2023, pp. 22113-22136. [PMLR] [ArXiv]
- Human-in-the-Loop Video Semantic Segmentation Auto-Annotation
Nan Qiao, Yuyin Sun, Chong Liu, Lu Xia, Jiajia Luo, Ke Zhang, and Cheng-Hao Kuo.
The 10th IEEE/CVF Winter Conference on Applications of Computer Vision (WACV-2023), Waikoloa, HI, 2023, pp. 5881-5891. [CVF]
- Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning
Chong Liu, Yuqing Zhu, Kamalika Chaudhuri, and Yu-Xiang Wang.
The 24th International Conference on Artificial Intelligence and Statistics (AISTATS-2021), San Diego, CA, 2021, pp. 838-846. [PMLR] [ArXiv]
- Dual Set Multi-Label Learning
Chong Liu, Peng Zhao, Sheng-Jun Huang, Yuan Jiang, and Zhi-Hua Zhou.
The 32nd AAAI Conference on Artificial Intelligence (AAAI-2018), New Orleans, LA, 2018, pp. 3635-3642. [Oral presentation] [Paper] [Supp.] [Slides] [Code]
Journal
- Doubly Robust Crowdsourcing
Chong Liu and Yu-Xiang Wang.
Journal of Artificial Intelligence Research (JAIR), 73:209-229, 2022. [JAIR] [ArXiv] [Code]
- Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning
Chong Liu, Yuqing Zhu, Kamalika Chaudhuri, and Yu-Xiang Wang.
Journal of Machine Learning Research (JMLR), 22(262):1−44, 2021. [JMLR] [ArXiv] [Code]
Workshop
- Cost-Sensitive Experimental Design for Atomistic Modeling
Chong Liu, Anirudh Raju Natarajan, Derick Evan Ober, Anton Van der Ven, and Yu-Xiang Wang.
ICML Workshop on Adaptive Experimental Design and Active Learning in the Real World (ReALML-2022), Baltimore, MD, 2022. [Paper]
- Model-Agnostic Private Learning with Domain Adaptation
Yuqing Zhu, Chong Liu, and Yu-Xiang Wang.
CCS Workshop on Theory and Practice of Differential Privacy (TPDP-2020), Orlando, FL, 2020.