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ALR-HT: A fast and efficient Lasso regression without hyperparameter tuning Journal article
Wang, Yuhang, Zou, Bin, Xu, Jie, Xu, Chen, Tang, Yuan Yan. ALR-HT: A fast and efficient Lasso regression without hyperparameter tuning[J]. Neural Networks, 2025, 181.
Authors:  Wang, Yuhang;  Zou, Bin;  Xu, Jie;  Xu, Chen;  Tang, Yuan Yan
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:6.0/7.9 | Submit date：2025/01/22
Additive Models  Generalization Bound  Hyperparameter Tuning  Lasso Regression  Markov Resampling  Ridge Regression  
Noise Robust Face Hallucination Based on Smooth Correntropy Representation Journal article
Licheng Liu, Qiying Feng, C. L. Philip Chen, Yaonan Wang. Noise Robust Face Hallucination Based on Smooth Correntropy Representation[J]. IEEE Transactions on Neural Networks and Learning Systems, 2022, 33(10), 5953-5965.
Authors:  Licheng Liu;  Qiying Feng;  C. L. Philip Chen;  Yaonan Wang
Favorite | TC[WOS]:12 TC[Scopus]:17  IF:10.2/10.4 | Submit date：2022/05/13
Correntropy-induced Metric (Cim)  Faces  Fused Lasso Penalty  Image Reconstruction  Manifolds  Noise Measurement  Noise Robustness  Smooth Representation  Sparse Regression.  Superresolution  Training  
Lasso for sparse linear regression with exponentially β-mixing errors Journal article
Xie,Fang, Xu,Lihu, Yang,Youcai. Lasso for sparse linear regression with exponentially β-mixing errors[J]. STATISTICS & PROBABILITY LETTERS, 2017, 125, 64-70.
Authors:  Xie,Fang;  Xu,Lihu;  Yang,Youcai
Favorite | TC[WOS]:5 TC[Scopus]:5 | Submit date：2019/06/03
Consistency  Exponentially Β-mixing Errors  Lasso  Linear Regression Models  
Lasso for sparse linear regression with exponentially beta-mixing errors Journal article
Xie, Fang, Xu, Lihu, Yang, Youcai. Lasso for sparse linear regression with exponentially beta-mixing errors[J]. STATISTICS & PROBABILITY LETTERS, 2017, 125, 64-70.
Authors:  Xie, Fang;  Xu, Lihu;  Yang, Youcai
Favorite | TC[WOS]:5 TC[Scopus]:5  IF:0.9/0.8 | Submit date：2018/10/30
Lasso  Linear Regression Models  Consistency  Exponentially Beta-mixing Errors