Xiang-Yu Hua

发表

Robust support vector regression with generic quadratic nonconvex ε-insensitive loss

Ya-Fen Ye, Junbin Gao, Y. Shao, 2020 .

Indicator Selection of Index Construction by Adaptive Lasso with a Generic e -Insensitive Loss

Ya-Fen Ye, Y. Shao, Chunna Li, 2021 .

Online support vector quantile regression for the dynamic time series with heavy-tailed noise

Ya-Fen Ye, Xiang-Yu Hua, Yuan-Hai Shao, 2021, Appl. Soft Comput..

Weighted Lagrange ε-twin support vector regression

Lan Bai, Yuan-Hai Shao, Zhen Wang, 2016, Neurocomputing.

Indicator Selection of Index Construction by Adaptive Lasso with a Generic $$\varepsilon $$-Insensitive Loss

Chun-Na Li, Renyong Chi, Yafen Ye, 2021, Computational Economics.

Feature selection for high‐dimensional regression via sparse LSSVR based on Lp ‐norm

Yuan-Hai Shao, Chun-Na Li, Da Zhao, 2020, Int. J. Intell. Syst..

Combined outputs framework for twin support vector machines

N. Deng, Y. Shao, Xiang-Yu Hua, 2015, Applied intelligence (Boston).

Robust Lp-norm least squares support vector regression with feature selection

Yuan-Hai Shao, Chun-Na Li, Nai-Yang Deng, 2017, Appl. Math. Comput..

A novel parametric-insensitive nonparallel support vector machine for regression

Yuan-Hai Shao, Ya-Fen Ye, Zhi-Min Yang, 2016, Neurocomputing.

A Novel Dynamic Financial Conditions Index Approach Based on Accurate Online Support Vector Regression

Yuan-Hai Shao, Ya-Fen Ye, Zhi-Min Yang, 2015, ITQM.