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Caixing Wang, Tao Li, Xinyi Zhang, Xingdong Feng & Xin He. (2024) Communication-Efficient Nonparametric Quantile Regression via Random Features. Journal of Computational and Graphical Statistics 0:0, pages 1-10.
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Haixiang Zhang, Lulu Zuo, HaiYing Wang & Liuquan Sun. (2024) Approximating Partial Likelihood Estimators via Optimal Subsampling. Journal of Computational and Graphical Statistics 33:1, pages 276-288.
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Yingying Ma, Chenlei Leng & Hansheng Wang. (2024) Optimal Subsampling Bootstrap for Massive Data. Journal of Business & Economic Statistics 42:1, pages 174-186.
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Tony Sit & Yue Xing. (2023) Distributed Censored Quantile Regression. Journal of Computational and Graphical Statistics 32:4, pages 1685-1697.
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Canyi Chen & Liping Zhu. (2023) Distributed Decoding From Heterogeneous 1-Bit Compressive Measurements. Journal of Computational and Graphical Statistics 32:3, pages 884-894.
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Xudong Zhang, Ting Zhang & Lei Wang. (2023) Two-stage communication-efficient distributed sparse M-estimation with missing data. Statistics 57:3, pages 617-636.
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Xingxiang Li & Chen Xu. (2023) Feature Screening with Conditional Rank Utility for Big-Data Classification. Journal of the American Statistical Association 0:0, pages 1-11.
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Xuetong Li, Yuan Gao, Hong Chang, Danyang Huang, Yingying Ma, Rui Pan, Haobo Qi, Feifei Wang, Shuyuan Wu, Ke Xu, Jing Zhou, Xuening Zhu, Yingqiu Zhu & Hansheng Wang. A selective review on statistical methods for massive data computation: distributed computing, subsampling, and minibatch techniques. Statistical Theory and Related Fields 0:0, pages 1-23.
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Kuo Gai & Shihua Zhang. (2024) Tessellating the Latent Space for Non-Adversarial Generative Auto-Encoders. IEEE Transactions on Pattern Analysis and Machine Intelligence 46:2, pages 780-792.
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Yimeng Ren, Zhe Li, Xuening Zhu, Yuan Gao & Hansheng Wang. (2024) Distributed estimation and inference for spatial autoregression model with large scale networks. Journal of Econometrics 238:2, pages 105629.
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Nemanja Petrović, Dragana Bajović, Soummya Kar, Dušan Jakovetić & Anit Kumar Sahu. (2023) Large Deviations for Products of Non-Identically Distributed Network Matrices With Applications to Communication-Efficient Distributed Learning and Inference. IEEE Transactions on Signal Processing 71, pages 1319-1333.
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Zhengtian Zhu & Liping Zhu. (2022) Distributed dimension reduction with nearly oracle rate. Statistical Analysis and Data Mining: The ASA Data Science Journal 15:6, pages 692-706.
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Kangqiang Li, Han Bao & Lixin Zhang. (2021) Robust covariance estimation for distributed principal component analysis. Metrika 85:6, pages 707-732.
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Xiaokang Liu, Rui Duan, Chongliang Luo, Alexis Ogdie, Jason H. Moore, Henry R. Kranzler, Jiang Bian & Yong Chen. (2022) Multisite learning of high-dimensional heterogeneous data with applications to opioid use disorder study of 15,000 patients across 5 clinical sites. Scientific Reports 12:1.
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