第一作者及通讯作者论文：
Zhao-Rong Lai, Weiwen Wang, “Invariant Risk Minimization Is A Total Variation Model”, the 41st International Conference on Machine Learning (ICML, main track), 2024.（机器学习两大国际顶级会议之一，中国计算机学会A类会议）
Zhao-Rong Lai, Xiaotian Wu, Liangda Fang, Ziliang Chen, “A De-singularity Subgradient Approach for the Extended Weber Location Problem”, International Joint Conference on Artificial Intelligence (IJCAI, main track), 2024.（人工智能两大国际顶级会议之一，中国计算机学会A类会议）
Yizun Lin, Zhao-Rong Lai*, Cheng Li, “A Locally Optimal Portfolio for m-Sparse Sharpe Ratio Maximization”, the 38th Annual Conference on Neural Information Processing Systems（NeurIPS, main track), 2024.（机器学习两大国际顶级会议之二，中国计算机学会A类会议）
Yizun Lin, Yangyu Zhang, Zhao-Rong Lai*, Cheng Li, “Autonomous Sparse Mean-CVaR Portfolio Optimization”, the 41st International Conference on Machine Learning (ICML, main track), 2024.（机器学习两大国际顶级会议之一，中国计算机学会A类会议）
Zhao-Rong Lai, Liming Tan, Shaoling Chen, Haisheng Yang, “Sparse-structured time-varying parameter vector autoregression for high-dimensional network connectedness measurement”, Expert Systems with Applications, vol. 258,no. 125136,2024.（影响因子7.5，中科院SCI一区TOP期刊，中国计算机学会C类期刊）
Z. R. Lai, C. Li, X. Wu, Q. Guan, L. Fang, “Multi-trend Conditional Value at Risk for Portfolio Optimization”, IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 2, pp. 1545-1558, Feb. 2024.（影响因子10.451，中科院SCI一区国际顶级期刊，中国计算机学会B类期刊）
Z. R. Lai，H. Yang， “A Survey on Gaps between Mean-variance Approach and Exponential Growth Rate Approach for Portfolio Optimization”，ACM Computing Surveys (CSUR), vol. 55, no. 2, pp. 1–36, Mar. 2023, Article No. 25.（计算机综述类顶级期刊，中科院SCI一区TOP期刊，影响因子23.8）
Z. R. Lai，L. Tan, X. Wu，L. Fang， “Loss Control with Rank-one Covariance Estimate for Short-term Portfolio Optimization”，Journal of Machine Learning Research (JMLR), vol. 21, no. 97, pp. 1-37, Jun. 2020.（人工智能与机器学习领域的四大国际顶级期刊之一，机器学习领域的顶级期刊，中国计算机学会A类、中国数学会T1双顶级期刊。影响因子4.091。）
Z. R. Lai，P. Y. Yang, L. Fang，X. Wu， “Short-term Sparse Portfolio Optimization Based on Alternating Direction Method of Multipliers”，Journal of Machine Learning Research (JMLR), vol. 19, no. 63, pp. 1-28, Oct. 2018.（人工智能与机器学习领域的四大国际顶级期刊之一，机器学习领域的顶级期刊，中国计算机学会A类、中国数学会T1双顶级期刊。影响因子4.091。）
Z. R. Lai, D. Q. Dai, C.X. Ren, K. K. Huang, “Radial basis functions with adaptive input and composite trend representation for portfolio selection”, IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 12, pp. 6214–6226, Dec. 2018.（影响因子11.683，中科院SCI一区国际顶级期刊，中国计算机学会B类期刊）
Z. R. Lai, D. Q. Dai, C.X. Ren, K. K. Huang, “A peak price tracking based learning system for portfolio selection”, IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 7, pp. 2823–2832, Jul. 2018.（影响因子11.683，中科院SCI一区国际顶级期刊，中国计算机学会B类期刊）
Z. R. Lai，P. Y. Yang，L. Fang， X. Wu， “Reweighted Price Relative Tracking System for Automatic Portfolio Optimization”，IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 50, no. 11, pp. 4349–4361, Nov. 2020. （影响因子13.451，中科院SCI一区期刊和TOP期刊）
Z. R. Lai，P. Y. Yang，X. Wu，L. Fang， “A Kernel-based Trend Pattern Tracking System for Portfolio Optimization”，Data Mining and Knowledge Discovery, vol. 32, no. 6, pp. 1708–1734, 2018.（影响因子2.481，中科院SCI二区国际核心期刊，中国计算机学会B类期刊，数据挖掘权威期刊）
Z. R. Lai, D. Q. Dai, C. X. Ren, and K. K. Huang. “Discriminative and compact coding for robust face recognition,” IEEE Transactions on Cybernetics, vol. 45, no. 9, pp. 1900–1912, Sept. 2015. (影响因子10.387, 中科院SCI一区国际顶级期刊)
Z. R. Lai, D. Q. Dai, C. X. Ren, and K. K. Huang. “Multiscale logarithm difference edgemaps for face recognition against varying lighting conditions”, IEEE Transactions on Image Processing, vol. 24, no. 6, pp. 1735–1747, June 2015. (影响因子6.790, 中科院SCI二区国际核心期刊和TOP期刊，中国计算机学会A类期刊)
Z. R. Lai, D. Q. Dai, C. X. Ren, and K. K. Huang. “Multilayer surface albedo for face recognition with reference images in bad lighting conditions,” IEEE Transactions on Image Processing, vol. 23, no. 11, pp. 4709–4723, Nov. 2014. (影响因子6.790，中科院SCI二区国际核心期刊和TOP期刊，中国计算机学会A类期刊)
X.-b. Ye, Q. Guan,W. Luo,L. Fang,Z. R. Lai*,J. Wang“Molecular substructure graph attention network for molecular property identification in drug discovery”，Pattern Recognition, vol. 128, Article 108659, pp. 1-13, 2022.（影响因子7.740，中科院SCI一区国际顶级期刊，中国计算机学会B类期刊）
P. Y. Yang，Z. R. Lai*，X. Wu，L. Fang， “Trend representation based log-density regularization system for portfolio optimization”，Pattern Recognition, vol. 76, pp. 14-24, 2018.（影响因子5.898，中科院SCI二区国际核心期刊，中国计算机学会B类期刊）
如果需要论文的程序代码及数据集，请登录链接https://github.com/laizhr，
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或直接发邮件联系本人：
laizhr+at+jnu.edu.cn
谢谢！