Supplemental materials for “High-dimensional regression and classification under a class of convex loss functions”

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Supplemental materials for “High-dimensional regression and classification under a class of convex loss functions”

机译：关于“在一类凸损失函数下的高维回归和分类”的补充材料

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《Statistics and Its Interface》 |2013年第2期|共页
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中图分类统计学;
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入库时间 2022-08-18 13:46:50

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1. High-dimensional regression and classification under a class of convex loss functions [J] . YUAN JIANG, CHUNMING ZHANG Statistics and Its Interface . 2013,第2期

机译：一类凸损失函数下的高维回归与分类
2. High-dimensional regression and classification under a class of convex loss functions [J] . Yuan Jiang, Chunming Zhang Statistics and Its Interface . 2013,第2期

机译：一类凸损失函数下的高维回归与分类
3. Enhanced classification loss functions and regularization loss function (ECLFaRLF) algorithm for bowel cancer feature classification [J] . Trivedi Niraj, Alsadoon Abeer, Prasad P. W. C., Multimedia Tools and Applications . 2021,第14期

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4. GEV Regression with Convex Loss Applied to Imbalanced Binary Classification [C] . Haolin Zhang, Gongshen Liu, Li Pan, IEEE International Conference on Data Science in Cyberspace . 2016

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5. General Penalized Logistic Regression for Gene Selection in High-Dimensional Microarray Data Classification [D] . Bonney, Derrick Kwesi. 2020

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6. Covariance-regularized regression and classification for high-dimensional problems [O] . Daniela M. Witten, Robert Tibshirani -1

机译：高维问题的协方差正则化回归和分类
7. Boosting in the presence of outliers: adaptive classification with non-convex loss functions [O] . Li, Alexander Hanbo, Bradic, Jelena 2015

机译：在异常值存在的情况下提升：自适应分类非凸损失函数

Supplemental materials for “High-dimensional regression and classification under a class of convex loss functions”

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