High-dimensional Quantile Tensor Regression
报告人：Zhongyi Zhu (Fudan University)
时间：2022-09-30 10:00-11:00
地点：Tencent Meeting（511-589-604）
Abstract: Tensor data refers to data in the form of multidimensional arrays, which are widely available in many fields such as medical research, image analysis, recommendation systems, signal processing, network data, etc. In this talk, we study high-dimensional quantile regression with tensor covariates and proposed an estimator based on convex regularization and an estimator based on tensor decomposition. We also propose an alternating update algorithm combined with alternating direction method of multipliers (ADMM). The asymptotic properties of the estimators are established under suitable conditions. The numerical performances are demonstrated via simulations and an application to a crowd density estimation problem.
About the Speaker:
朱仲义，复旦大学统计系教授，博士生导师；曾任中国概率统计学会第八、九届副理事长,国际著名杂志《Statistica Sinica》副主编；《应用概率统计》和《数理统计与管理》杂志编委，中国统计教材编审委员会委员；现为 Elected ISI Member（国际统计学会推选会员），《中国科学:数学》杂志编委。研究方向包括保险精算、纵向数据(面板数据)模型、分位数回归模型等统计推断问题研究。目前主持国家自然科学基金重大项目子项目一项，重点项目子项目一项以及面上项目一项，已主持完成国家自然科学基金四项、国家社会科学基金一项。发表学术论文100多篇，包括在国际四大统计顶级刊物等SCI论文六十多篇，并获教育部自然科学二等奖一次。
Tencent Meeting：https://meeting.tencent.com/dm/sBfET2liiw2y
Meeting ID：511-589-604
