16 citations · 87 across the 30 of their papers we have counts for
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stat.CO2021★ 5 cited
Schr{ö}dinger-F{ö}llmer Sampler: Sampling without Ergodicity
Jian Huang, Yuling Jiao, Lican Kang +3
Sampling from probability distributions is an important problem in statistics and machine learning, specially in Bayesian inference when integration with respect to posterior distr…
stat.CO2018★ 1 cited
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…
stat.CO2017★ 3 cited
A Constructive Approach to High-dimensional Regression
Jian Huang, Yuling Jiao, Yanyan Liu +1
We develop a constructive approach to estimating sparse, high-dimensional linear regression models. The approach is a computational algorithm motivated from the KKT conditions for…