66 citations · 88 across the 9 of their papers we have counts for
9 papers
On Scalable Inference with Stochastic Gradient Descent
Yixin Fang, Jinfeng Xu, Lei Yang
In many applications involving large dataset or online updating, stochastic gradient descent (SGD) provides a scalable way to compute parameter estimates and has gained increasing…
Additive Partially Linear Models for Massive Heterogeneous Data
Binhuan Wang, Yixin Fang, Heng Lian +1
We consider an additive partially linear framework for modelling massive heterogeneous data. The major goal is to extract multiple common features simultaneously across all sub-pop…
Greedy Criterion in Orthogonal Greedy Learning
Lin Xu, Shaobo Lin, Jinshan Zeng +2
Orthogonal greedy learning (OGL) is a stepwise learning scheme that starts with selecting a new atom from a specified dictionary via the steepest gradient descent (SGD) and then bu…
Penalized Weighted Least Squares for Outlier Detection and Robust Regression
Xiaoli Gao, Yixin Fang
To conduct regression analysis for data contaminated with outliers, many approaches have been proposed for simultaneous outlier detection and robust regression, so is the approach…
Flexible combination of multiple diagnostic biomarkers to improve diagnostic accuracy
Tu Xu, Yixin Fang, Alan Rong +1
In medical research, it is common to collect information of multiple continuous biomarkers to improve the accuracy of diagnostic tests. Combining the measurements of these biomarke…
A model-free estimation for the covariate-adjusted Youden index and its associated cut-point
Tu Xu, Junhui Wang, Yixin Fang
In medical research, continuous markers are widely employed in diagnostic tests to distinguish diseased and non-diseased subjects. The accuracy of such diagnostic tests is commonly…
A note on selection stability: combining stability and prediction
Yixin Fang, Junhui Wang, Wei Sun
Recently, many regularized procedures have been proposed for variable selection in linear regression, but their performance depends on the tuning parameter selection. Here a criter…
Consistent selection of tuning parameters via variable selection stability
Wei Sun, Junhui Wang, Yixin Fang
Penalized regression models are popularly used in high-dimensional data analysis to conduct variable selection and model fitting simultaneously. Whereas success has been widely rep…
A divergence formula for regularization methods with an L2 constraint
Yixin Fang, Yuanjia Wang, Xin Huang
We derive a divergence formula for a group of regularization methods with an L2 constraint. The formula is useful for regularization parameter selection, because it provides an unb…