[1]
|
Papageorgiou, G., Bouboulis, P. and Theodoridis, S. (2015) Robust Linear Regression Analysis—A Greedy Approach. IEEE Transactions on Signal Processing, 63, 3872-3887. https://doi.org/10.1109/TSP.2015.2430840
|
[2]
|
Huber, P. (1972) The 1972 Wald Lecture Robust Statistics: A Review. Annals of Mathematical Statistics, 43, 1041-1067. https://doi.org/10.1214/aoms/1177692459
|
[3]
|
Rousseeuw, P. and Leroy, A. (1987) Robust Regression and Outlier Detection. Wiley, New York, NY. https://doi.org/10.1002/0471725382
|
[4]
|
Maronna, R., Martin, R. and Yohai, V. (2006) Robust Statistics: Theory and Methods. Wiley, New York, NY.
|
[5]
|
Huber, P. (1981) Robust Statistics. Wiley, New York, NY.
|
[6]
|
Cook, R. and Weisberg, S. (1982) Residuals and Influence in Regression. Chapman and Hall, New York, NY.
|
[7]
|
Natarajan, B. (1995) Sparse Approximate Solutions to Linear Systems. SIAM Journal on Computing, 24, 227-234. https://doi.org/10.1137/S0097539792240406
|
[8]
|
Nguyen, N. and Tran, T. (2013) Robust Lasso with Missing and Grossly Corrupted Observa- tions. IEEE Transactions on Information Theory, 59, 2036-2058. https://doi.org/10.1109/TIT.2012.2232347
|
[9]
|
Chen, J. and Liu, Y. (2019) Stable Recovery of Structured Signals from Corrupted Subgaussian Measurements. IEEE Transactions on Information Theory, 65, 2976- 2994. https://doi.org/10.1109/TIT.2018.2890194
|
[10]
|
Katayama, S. and Fujisawa, H. (2017) Sparse and Robust Linear Regression: An Optimization Algorithm and Its Statistical Properties. Statistica Sinica, 27, 1243-1264. https://doi.org/10.5705/ss.202015.0179
|
[11]
|
Fan, J. and Li, Y. (2001) Variable Selection via Nonconcave Penalized Likelihood and Its Oracle Properties. Journal of the American Statistical Association, 96, 1348-1360. https://doi.org/10.1198/016214501753382273
|
[12]
|
Ong, C. and An, L. (2013) Learning Sparse Classifiers with Difference of Convex Functions Algorithms. Optimization Methods and Software, 28, 830-854. https://doi.org/10.1080/10556788.2011.652630
|
[13]
|
Peleg, D. and Meir, R. (2008) A Bilinear Formulation for Vector Sparsity Optimization. Signal Processing, 88, 375-389. https://doi.org/10.1016/j.sigpro.2007.08.015
|
[14]
|
Zhang, C. (2010) Nearly Unbiased Variable Selection under Minimax Concave Penalty. Annals of Statistics, 38, 894-942. https://doi.org/10.1214/09-AOS729
|
[15]
|
Zhang, T. (2010) Analysis of Multi-Stage Convex Relaxation for Sparse Regularization. Journal of Machine Learning Research, 11, 1081-1107.
|
[16]
|
Cand´es, E., Romberg, J. and Tao, T. (2006) Robust Uncertainty Principles: Exact Signal Reconstruction from Highly Incomplete Frequency Information. IEEE Transactions on Infor- mation Theory, 52, 489-509. https://doi.org/10.1109/TIT.2005.862083
|
[17]
|
Huber, P. (1964) Robust Estimation of a Location Parameter. Annals of Mathematical Statis- tics, 35, 73-101. https://doi.org/10.1214/aoms/1177703732
|
[18]
|
Fan, J., Li, Q. and Wang, Y. (2017) Estimation of High Dimensional Mean Regression in the Absence of Symmetry and Light Tail Assumptions. Journal of Royal Statistical Society, Series B, 79, 247-265. https://doi.org/10.1111/rssb.12166
|
[19]
|
Yi, C. and Huang, J. (2017) Semismooth Newton Coordinate Descent Algorithm for Elastic- Net Penalized Huber Loss Regression and Quantile Regression. Journal of Computational and Graphical Statistics, 26, 547-557. https://doi.org/10.1080/10618600.2016.1256816
|
[20]
|
[20] Sun, Q., Zhou, W. and Fan, J. (2020) Adaptive Huber Regression. Journal of the American Statistical Association, 115, 254-265. https://doi.org/10.1080/01621459.2018.1543124
|
[21]
|
Peng, D. and Chen, X. (2020) Computation of Second-Order Directional Stationary Points for Group Sparse Optimization. Optimization Methods and Software, 35, 348-376. https://doi.org/10.1080/10556788.2019.1684492
|
[22]
|
Zhang, X. and Peng, D. (2022) Solving Constrained Nonsmooth Group Sparse Optimization via Group Capped-L1 Relaxation and Group Smoothing Proximal Gradient Algorithm. Com- putational Optimization and Applications, 83, 801-844. https://doi.org/10.1007/s10589-022-00419-2
|
[23]
|
彭定涛, 唐琦, 张弦. 组稀疏优化问题精确连续Capped-L1松弛[J]. 数学学报, 2022, 65(2): 243-262.
|
[24]
|
罗孝敏, 彭定涛, 张弦. 基于MCP正则的最小一乘回归问题研究[J]. 系统科学与数学, 2021, 41(8): 2327-2337.
|
[25]
|
Ahn, M., Pang, J. and Jack, X. (2017) Difference-of-Convex Learning: Directional Stationarity, Optimality, and Sparsity. SIAM Journal on Optimization, 27, 1637-1665. https://doi.org/10.1137/16M1084754
|
[26]
|
Chen, X., Niu, L. and Yuan, Y. (2013) Optimality Conditions and a Smoothing Trust Region Newton Method for Non-Lipschitz Optimization. SIAM Journal on Optimization, 23, 1528- 1552. https://doi.org/10.1137/120871390
|