6 papers
Distributed Stochastic Smoothing ADMM for Penalized Quantile Regression
Rongmei Liang, Xiaofei Wu
Quantile regression is well suited to heterogeneous and heavy-tailed data, but computation becomes challenging for large, distributed data sets because the check loss is nonsmooth.…
Data-Driven Pinball-Loss Selection for Vertically Distributed Elastic-Net SVMs
Xiaofei Wu, Kai Qi, Rongmei Liang
The pinball-loss support vector machine is robust, but its asymmetry parameter is usually fixed in advance. We propose a data-driven elastic-net support vector machine that learns…
Leveraging Noisy Manual Labels as Useful Information: An Information Fusion Approach for Enhanced Variable Selection in Penalized Logistic Regression
Xiaofei Wu, Rongmei Liangse
In large-scale supervised learning, penalized logistic regression (PLR) effectively mitigates overfitting through regularization, yet its performance critically depends on robust v…
Parallel Algorithms for Structured Sparse Support Vector Machines: Application in Music Genre Classification
Rongmei Liang, Zizheng Liu, Xiaofei Wu +1
Mathematical modelling, particularly through approaches such as structured sparse support vector machines (SS-SVM), plays a crucial role in processing data with complex feature str…
Feature splitting parallel algorithm for Dantzig selectors
Xiaofei Wu, Yue Chao, Rongmei Liang +2
The Dantzig selector is a widely used and effective method for variable selection in ultra-high-dimensional data. Feature splitting is an efficient processing technique that involv…
Parallel ADMM Algorithm with Gaussian Back Substitution for High-Dimensional Quantile Regression and Classification
Xiaofei Wu, Dingzi Guo, Rongmei Liang +1
In the field of high-dimensional data analysis, modeling methods based on quantile loss function are highly regarded due to their ability to provide a comprehensive statistical per…