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Guo, Wenxing and Zhang, Xueying and Jiang, Bei and Kong, Linglong and Hu, Yaozhong (2023) Wavelet‑based Bayesian approximate kernel method for high‑dimensional data analysis. Computational Statistics, 39 (4). pp. 2323-2341. DOI https://doi.org/10.1007/s00180-023-01438-1
Guo, Wenxing and Balakrishnan, Narayanaswamy and He, Mu (2023) Envelope-based sparse reduced-rank regression for multivariate linear model. Journal of Multivariate Analysis, 195. p. 105159. DOI https://doi.org/10.1016/j.jmva.2023.105159 (In Press)
Guo, Wenxing and Balakrishnan, Narayanaswamy and Qin, Shanshan (2023) A modified partial envelope tensor response regression. Stat, 12 (1). e615. DOI https://doi.org/10.1002/sta4.615
Ding, Lei and Yu, Dengdeng and Xie, Jinhan and Guo, Wenxing and Hu, Shenggang and Liu, Meichen and Kong, Linglong and Dai, Hongsheng and Bao, Yanchun and Jiang, Bei (2022) Word Embeddings via Causal Inference: Gender Bias Reducing and Semantic Information Preserving. In: Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22), 2022-02-22 - 2022-03-01, Vancouver. (In Press)
Guo, Wenxing and Balakrishnan, Narayanaswamy and Bian, Mengjie (2021) Reduced rank regression with matrix projections for high-dimensional multivariate linear regression model. Electronic Journal of Statistics, 15 (2). pp. 4167-4191. DOI https://doi.org/10.1214/21-ejs1895