Zhang, Yehong

11 publications

TMLR 2024 Dependency Structure Search Bayesian Optimization for Decision Making Models Mohit Rajpal, Lac Gia Tran, Yehong Zhang, Bryan Kian Hsiang Low

AAAI 2024 EncryIP: A Practical Encryption-Based Framework for Model Intellectual Property Protection Xin Mu, Yu Wang, Zhengan Huang, Junzuo Lai, Yehong Zhang, Hui Wang, Yue Yu

IJCAI 2024 Meta-Learning via PAC-Bayesian with Data-Dependent Prior: Generalization Bounds from Local Entropy Shiyu Liu, Wei Shi, Zenglin Xu, Shaogao Lv, Yehong Zhang, Hui Wang

NeurIPS 2023 Incentives in Private Collaborative Machine Learning Rachael Sim, Yehong Zhang, Nghia Hoang, Xinyi Xu, Bryan Kian Hsiang Low, Patrick Jaillet

UAI 2023 Practical Privacy-Preserving Gaussian Process Regression via Secret Sharing Jinglong Luo, Yehong Zhang, Jiaqi Zhang, Shuang Qin, Hui Wang, Yue Yu, Zenglin Xu

MLJ 2023 Pruning During Training by Network Efficacy Modeling Mohit Rajpal, Yehong Zhang, Bryan Kian Hsiang Low

ICML 2021 Collaborative Bayesian Optimization with Fair Regret Rachael Hwee Ling Sim, Yehong Zhang, Bryan Kian Hsiang Low, Patrick Jaillet

ICML 2020 Collaborative Machine Learning with Incentive-Aware Model Rewards Rachael Hwee Ling Sim, Yehong Zhang, Mun Choon Chan, Bryan Kian Hsiang Low

AAAI 2020 Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression Tong Teng, Jie Chen, Yehong Zhang, Bryan Kian Hsiang Low

UAI 2019 Bayesian Optimization with Binary Auxiliary Information Yehong Zhang, Zhongxiang Dai, Bryan Kian Hsiang Low

AAAI 2016 Near-Optimal Active Learning of Multi-Output Gaussian Processes Yehong Zhang, Trong Nghia Hoang, Kian Hsiang Low, Mohan S. Kankanhalli