7 citations · 11 across the 5 of their papers we have counts for
5 papers
Phase transition and higher order analysis of regularization under dependence
Hanwen Huang, Peng Zeng, Qinglong Yang
We study the problem of estimating a -sparse signal ${\mbox{$β$}}_0\in{\bf R}^p$ from a set of noisy observations under the model ${\bf y}={\bf X}{\mbox{$β…
Large scale analysis of generalization error in learning using margin based classification methods
Hanwen Huang, Qinglong Yang
Large-margin classifiers are popular methods for classification. We derive the asymptotic expression for the generalization error of a family of large-margin classifiers in the lim…
Large dimensional analysis of general margin based classification methods
Hanwen Huang, Qinglong Yang
Margin-based classifiers have been popular in both machine learning and statistics for classification problems. Since a large number of classifiers are available, one natural quest…
SNAP: A semismooth Newton algorithm for pathwise optimization with optimal local convergence rate and oracle properties
Jian Huang, Yuling Jiao, Xiliang Lu +2
We propose a semismooth Newton algorithm for pathwise optimization (SNAP) for the LASSO and Enet in sparse, high-dimensional linear regression. SNAP is derived from a suitable form…
A Semi-Smooth Newton Algorithm for High-Dimensional Nonconvex Sparse Learning
Yueyong Shi, Jian Huang, Yuling Jiao +1
The smoothly clipped absolute deviation (SCAD) and the minimax concave penalty (MCP) penalized regression models are two important and widely used nonconvex sparse learning tools t…