Zuofeng Shang

Wang, Shuoyang, & Cao, Guanqun, & Shang, Zuofeng (2023). Deep Neural Network Classifier for Multi-dimensional Functional Data. Scandinavian Journal of Statistics,

Liu, Ruiqi, & Xu, Ganggang, & Shang, Zuofeng (2023). Distributed Adaptive Nearest Neighbor Classifier: Algorithm and Theory. Statistics and Computing,

Zhang, Hewei, & Li, Qin , & Yang, Yixin, & Jing, Ju, & Wang, Jason T., & Wang, Haimin, & Shang, Zuofeng (2022). Solar Flare Index Prediction Using SDO/HMI Vector Magnetic Data Products with Statistical and Machine-learning Methods. ApJ, 263, 28.

Yuan, Mingao, & Feng, Yang, & Shang, Zuofeng (2022). A likelihood-ratio type test for stochastic block models with bounded degrees. Journal of Statistical Planning and Inference,

Zhang, Hewei, & Li, Qin, & Yang, Yanxing, & Ju, Jing, & Wang, Jason, & Wang, Haimin, & Shang, Zuofeng (2022). Solar Flare Index Prediction Using SDO/HMI Vector Magnetic Data Products with Statistical and Machine Learning Methods. The Astrophysical Journal Supplement,

Wang, Shuoyang, & Shang, Zuofeng (2022). Minimax Optimal High-Dimensional Classification using Deep Neural Networks. Stat,

Dai, Xiaotian, & Fu, Guifang, & Reese, Randall, & Zhao, Shaofei, & Shang, Zuofeng (2022). An Approach of Bayesian Variable Selection for Ultrahigh Dimensional Multivariate Regression. STAT,

Liu, Ruiqi, & Yuan, Mingao, & Shang, Zuofeng (2022). Online statistical inference for parameters estimation with linear-equality constraints   . Journal of Multivariate Analysis   ,

Wang, Shuoyang , & Cao, Guanqun, & Shang, Zuofeng (2021). Estimation of the Mean Function of Functional Data via Deep Neural Networks. Stat,

Yuan, Mingao, & Yang, Fan Emily, & Shang, Zuofeng (2021). Hypothesis Testing in Sparse Weighted Stochastic Block Model. Statistical Papers,

Yuan, Mingao, & Shang, Zuofeng (2021). Information Limits for Detecting a Subhypergraph. STAT,

Yuan, Mingao, & Shang, Zuofeng (2021). Sharp Detection Boundaries on Testing Dense Subhypergraph. Bernoulli,

Yuan, Mingao, & Liu, Ruiqi, & Feng, Yang, & Shang, Zuofeng (2021). Testing Community Structures for Hypergraph Models. Annals of Statistics,

Liu, Ruiqi, & Boukai, Ben, & Shang, Zuofeng (2021). Optimal Nonparametric Inference via Deep Neural Network. Journal of Mathematical Analysis and Applications,

Liu, Meimei, & Shang, Zuofeng, & Yang, Yun, & Cheng, Guang (2021). Nonparametric Testing under Randomized Sketching. IEEE Transactions on Pattern Analysis and Machine Intelligence,

Liu, Meimei, & Shang, Zuofeng, & Cheng, Guang (2020). Nonparametric Distributed Learning under Random Design. Electronic Journal of Statistics,

Liu, Ruiqi, & Shang, Zuofeng, & Zhang, Yonghui, & Zhou, Qiankun (2020). Identification and estimation in panel models with overspecified number of groups. Journal of Econometrics,

Xu, Ganggang, & Shang, Zuofeng, & Cheng, Guang (2019). Distributed Generalized Cross-Validation for Divide-and-Conquer Kernel Ridge Regression and its Asymptotic Optimality. Journal of Computational and Graphical Statistics,

Shang, Zuofeng, & Hao, Botao, & Cheng, Guang (2019). Nonparametric Bayesian Aggregation for Massive Data. Journal of Machine Learning Research,

Zhao, Shunan, & Liu, Ruiqi, & Shang, Zuofeng (2019). Statistical Inference on Panel Data Models: A Kernel Ridge Regression Method. Journal of Business & Economic Statistics ,

Temporal Bipartite Graph Neural Networks for Bond Prediction
November 2022

Temporal Bipartite Graph Neural Networks for Predicting Financial Time Series with Irregular Intervals
ICDM/SSTDM 2022 : 17th International Workshop on Spatial and Spatiotemporal Data Mining, October (4th Quarter/Autumn) 2022

Non-asymptotic Theory for Nonparametric Testing
33rd Annual Conference on Learning Theory, 2020

Probabilistic Connection Importance Inference and Lossless Compression of Deep Neural Networks
The International Conference on Learning Representations (ICLR) 2020, 2020

Sharp Theoretical Analysis for Nonparametric Testing under Random Projection
32nd Annual Conference on Learning Theory, 2019