Learning from uniformly ergodic Markov chains. - Bin Zou 002; Hai Zhang 001; Zongben Xu (J. Complex., 2009)

L1/2 regularization. - Zongben Xu; Hai Zhang 001; Yao Wang 003; Xiangyu Chang; Yong Liang 001 (Sci. China Inf. Sci., 2010)

Generalization Bounds of Regularization Algorithms Derived Simultaneously through Hypothesis Space Complexity, Algorithmic Stability and Data Quality. - Xiangyu Chang; Zongben Xu; Bin Zou 002; Hai Zhang 001 (Int. J. Wavelets Multiresolution Inf. Process., 2011)

Iterative L1/2 Regularization Algorithm for Variable Selection in the Cox Proportional Hazards Model. - Cheng Liu; Yong Liang 001; Xin-Ze Luan; Kwong-Sak Leung; Tak-Ming Chan; Zongben Xu; Hai Zhang 001 (ICSI (2), 2012)

Regularization Path for Linear Model via Net Method. - Xin-Ze Luan; Yong Liang 001; Cheng Liu; Zongben Xu; Hai Zhang 001; Kwong-Sak Leung; Tak-Ming Chan (ICSI (2), 2012)

The essential ability of sparse reconstruction of different compressive sensing strategies. - Hai Zhang 001; Yong Liang 001; HaiLiang Gou; Zongben Xu (Sci. China Inf. Sci., 2012)

Asymptotic Normality of Maximum Likelihood and its Variational Approximation for Stochastic Blockmodels - Peter J. Bickel; David Choi; Xiangyu Chang; Hai Zhang 001 (CoRR, 2012)

L1/2 Regularization: A Thresholding Representation Theory and a Fast Solver. - Zongben Xu; Xiangyu Chang; Fengmin Xu; Hai Zhang 001 (IEEE Trans. Neural Networks Learn. Syst., 2012)

Sparse logistic regression with a L1/2 penalty for gene selection in cancer classification. - Yong Liang 001; Cheng Liu; Xin-Ze Luan; Kwong-Sak Leung; Tak-Ming Chan; Zongben Xu; Hai Zhang 001 (BMC Bioinform., 2013)

The L1/2 regularization method for variable selection in the Cox model. - Cheng Liu; Yong Liang 001; Xin-Ze Luan; Kwong-Sak Leung; Tak-Ming Chan; Zongben Xu; Hai Zhang 001 (Appl. Soft Comput., 2014)

A novel L1/2 regularization shooting method for Cox's proportional hazards model. - Xin-Ze Luan; Yong Liang 001; Cheng Liu; Kwong-Sak Leung; Tak-Ming Chan; Zongben Xu; Hai Zhang 001 (Soft Comput., 2014)

Sparse Bayesian linear regression using generalized normal priors. - Hai Zhang 001; Puyu Wang; Qing Dong; Pu Wang (Int. J. Wavelets Multiresolution Inf. Process., 2017)

A Novel Data Clustering Method Based on Smooth Non-negative Matrix Factorization. - Chengcai Leng; Hai Zhang 001; Guorong Cai (ICSM, 2018)

Distributed Logistic Regression for Separated Massive Data. - Peishen Shi; Puyu Wang; Hai Zhang 001 (Big Data (CCF), 2019)

Local Feature Descriptor for Image Matching: A Survey. - Chengcai Leng; Hai Zhang 001; Bo Li 023; Guorong Cai; Zhao Pei; Li He 002 (IEEE Access, 2019)

Approximate Message Passing Algorithm for Nonconvex Regularization. - Hui Zhang 032; Hai Zhang 001; Yong Liang 001; Ziyi Yang; Yanqiong Ren (IEEE Access, 2019)

Differentially Private Precision Matrix Estimation. - Wenqing Su; Xiao Guo; Hai Zhang 001 (CoRR, 2019)

Structure learning of sparse directed acyclic graphs incorporating the scale-free property. - Xiao Guo; Hai Zhang 001; Yao Wang 003; Yong Liang 001 (Comput. Stat., 2019)

Graph regularized Lp smooth non-negative matrix factorization for data representation. - Chengcai Leng; Hai Zhang 001; Guorong Cai; Irene Cheng 001; Anup Basu (IEEE CAA J. Autom. Sinica, 2019)

Differential privacy for sparse classification learning. - Puyu Wang; Hai Zhang 001 (Neurocomputing, 2020)

Novel Regularization Method for Biomarker Selection and Cancer Classification. - Xiao-Ying Liu 003; Sai Wang; Hai Zhang 001; Hui Zhang 032; Ziyi Yang; Yong Liang 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

Differentially Private SGD with Non-Smooth Loss. - Puyu Wang; Yunwen Lei; Yiming Ying; Hai Zhang 001 (CoRR, 2021)

Structured learning of time-varying networks with application to PM2.5 data. - Xiao Guo; Hai Zhang 001 (Commun. Stat. Simul. Comput., 2021)

Total Variation Constrained Non-Negative Matrix Factorization for Medical Image Registration. - Chengcai Leng; Hai Zhang 001; Guorong Cai; Zhen Chen; Anup Basu (IEEE CAA J. Autom. Sinica, 2021)

Differentially private empirical risk minimization for AUC maximization. - Puyu Wang; Zhenhuan Yang; Yunwen Lei; Yiming Ying; Hai Zhang 001 (Neurocomputing, 2021)

Enhancing performance of the back-propagation algorithm based on a novel regularization method of preserving inter-object-distance of data. - Junying Hu; Kai Sun 007; Hai Zhang 001 (Int. J. Wavelets Multiresolution Inf. Process., 2021)

Helmholtz machine with differential privacy. - Junying Hu; Kai Sun 007; Hai Zhang 001 (Inf. Sci., 2022)

Randomized Spectral Clustering in Large-Scale Stochastic Block Models. - Hai Zhang 001; Xiao Guo; Xiangyu Chang (J. Comput. Graph. Stat., 2022)

UAMPnet: Unrolled approximate message passing network for nonconvex regularization. - Hui Zhang 032; Shoujiang Li; Yong Liang 001; Hai Zhang 001; Mengmeng Du (Expert Syst. Appl., 2023)

Privacy-preserving federated learning on lattice quantization. - Lingjie Zhang; Hai Zhang 001 (Int. J. Wavelets Multiresolution Inf. Process., 2023)

Randomized Spectral Co-Clustering for Large-Scale Directed Networks. - Xiao Guo; Yixuan Qiu; Hai Zhang 001; Xiangyu Chang (J. Mach. Learn. Res., 2023)

Shuffle Private Decentralized Convex Optimization. - Lingjie Zhang; Hai Zhang 001 (IEEE Trans. Inf. Forensics Secur., 2024)

On the efficacy of higher-order spectral clustering under weighted stochastic block models. - Xiao Guo; Hai Zhang 001; Xiangyu Chang (Comput. Stat. Data Anal., 2024)

Back-propagating errors through artificial neural networks for variable selection. - Junying Hu; Peiju Chang; Fang Du; Rongrong Fei; Kai Sun 007; Jiangshe Zhang 001; Hai Zhang 001 (Int. J. Wavelets Multiresolution Inf. Process., 2024)

Privacy-preserving communication-efficient spectral clustering for distributed multiple networks. - Shanghao Wu; Xiao Guo; Hai Zhang 001 (Comput. Stat. Data Anal., 2025)

Modified R-BERT with global semantic information for relation classification task. - Yuhua Wang; Junying Hu; Yongli Su; Bo Zhang; Kai Sun 007; Hai Zhang 001 (Comput. Speech Lang., 2025)

Efficient Over-parameterized Matrix Sensing from Noisy Measurements via Alternating Preconditioned Gradient Descent. - Zhiyu Liu; Zhi Han; Yandong Tang; Hai Zhang 001; Shaojie Tang 001; Yao Wang 003 (CoRR, 2025)