8 papers
Hybrid Federated Learning for Multimodal Fusion under Missing Modalities and Site Heterogeneity
Xiaofei Wu, Rongmei Liang, Jian Qing Shi
Multimodal fusion is studied under hybrid federation, where data are partitioned across samples and feature blocks. The proposed two-dimensional federated smooth multiple-kernel la…
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…
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…
A Partition-insensitive Parallel Framework for Distributed Model Fitting
Xiaofei Wu, Rongmei Liang, Fabio Roli +2
Distributed model fitting refers to the process of fitting a mathematical or statistical model to the data using distributed computing resources, such that computing tasks are divi…
Multi-block linearized alternating direction method for sparse fused Lasso modeling problems
Xiaofei Wu, Rongmei Liang, Zhimin Zhang +1
In many statistical modeling problems, such as classification and regression, it is common to encounter sparse and blocky coefficients. Sparse fused Lasso is specifically designed…