Efficient maximum approximated likelihood inference for Tukey's g-and-h distribution. - Ganggang Xu; Marc G. Genton (Comput. Stat. Data Anal., 2015)

Optimal Tuning for Divide-and-conquer Kernel Ridge Regression with Massive Data. - Ganggang Xu; Zuofeng Shang; Guang Cheng 003 (ICML, 2018)

Optimal Nonparametric Inference under Quantization. - Ruiqi Liu; Ganggang Xu; Zuofeng Shang (CoRR, 2019)

Borrowing strength and borrowing index for Bayesian hierarchical models. - Ganggang Xu; Huirong Zhu; J. Jack Lee (Comput. Stat. Data Anal., 2020)

Semi-parametric Learning of Structured Temporal Point Processes. - Ganggang Xu; Ming Wang; Jiangze Bian; Hui Huang; Timothy R. Burch; Sandro C. Andrade; Jingfei Zhang; Yongtao Guan (J. Mach. Learn. Res., 2020)

Row-clustering of a Point Process-valued Matrix. - Lihao Yin; Ganggang Xu; Huiyan Sang; Yongtao Guan (NeurIPS, 2021)

Distributed Adaptive Nearest Neighbor Classifier: Algorithm and Theory. - Ruiqi Liu; Ganggang Xu; Zuofeng Shang (CoRR, 2021)

Distributed adaptive nearest neighbor classifier: algorithm and theory. - Ruiqi Liu 003; Ganggang Xu; Zuofeng Shang (Stat. Comput., 2023)

Nonparametric Inference under B-bits Quantization. - Kexuan Li; Ruiqi Liu; Ganggang Xu; Zuofeng Shang (J. Mach. Learn. Res., 2024)