activity
20152026
most citedA Direct Approach for Sparse Quadratic Discriminant Analysis

20 citations · 64 across the 12 of their papers we have counts for

collaborators

12 papers

math.ST2026

Dynamic Networks with Node Heterogeneity and Homophily

Binyan Jiang, Qiwei Yao, Xinyang Yu

The goal of this paper is to model node heterogeneity and link homophily for dynamic networks. The proposed framework brings new insights on how networks evolve over time. It also…

stat.CO2023

HiQR: An efficient algorithm for high-dimensional quadratic regression with penalties

Cheng Wang, Haozhe Chen, Binyan Jiang

This paper investigates the efficient solution of penalized quadratic regressions in high-dimensional settings. A novel and efficient algorithm for ridge-penalized quadratic regres…

stat.ME2023

A two-way heterogeneity model for dynamic networks

Binyan Jiang, Chenlei Leng, Ting Yan +2

Dynamic network data analysis requires joint modelling individual snapshots and time dynamics. This paper proposes a new two-way heterogeneity model towards this goal. The new mode…

stat.ME2021★ 1 cited

Linear Discriminant Analysis with High-dimensional Mixed Variables

Binyan Jiang, Chenlei Leng, Cheng Wang +2

Datasets containing both categorical and continuous variables are frequently encountered in many areas, and with the rapid development of modern measurement technologies, the dimen…

stat.CO2021

MARS: A second-order reduction algorithm for high-dimensional sparse precision matrices estimation

Qian LI, Binyan Jiang, Defeng Sun

Estimation of the precision matrix (or inverse covariance matrix) is of great importance in statistical data analysis and machine learning. However, as the number of parameters sca…

stat.ME2020

Penalized estimation for single-index varying-coefficient models with applications to integrative genomic analysis

Hoi Min Ng, Binyan Jiang, Kin Yau Wong

Recent technological advances have made it possible to collect high-dimensional genomic data along with clinical data on a large number of subjects. In the studies of chronic disea…