• 演讲人： Dr. Peijun Sang（Waterloo University, Canada）
• 时间：2021年07月06日 周二下午3:00-4:00
• 地点：​浙江大学紫金港校区行政楼1417报告厅

• 演讲人：Dr. Peijun Sang（Waterloo University, Canada）
• 时间：2021年07月06日 周二下午3:00-4:00
• 地点：浙江大学紫金港校区行政楼1417报告厅
• 主办单位：数学科学学院、数据科学研究中心

Abstract: The intrinsic infinite-dimensional nature of functional data creates a bottleneck in the application of traditional classifiers to functional settings. These classifiers are generally either unable to generalize to infinite dimensions or have poor performance due to the curse of dimensionality. To address this concern, we propose building a distance-weighted discrimination (DWD) classifier on scores obtained by projecting data onto one specific direction. We choose this direction by minimizing, over a reproducing kernel Hilbert space, an empirical risk function containing the DWD classifier loss function. Our proposed classifier avoids overfitting and enjoys the appealing properties of DWD classifiers. We further extend this framework to accommodate functional data classification problems where scalar covariates are involved. In contrast to previous work, we establish a non-asymptotic estimation error bound on the relative misclassification rate. Through simulation studies and a real-world application, we demonstrate that the proposed classifier performs favorably relative to other commonly used functional classifiers in terms of prediction accuracy in finite-sample settings.

报告人简介

桑培俊， 2010年浙江大学本科毕业，2018年获Simon Fraser 大学统计学博士学位， 目前任加拿大Waterloo大学助理教授。主要研究方向是函数型数据，尤其是函数型数据分析中的统计推断问题，在Biometrics, Statistica Sinica, Journal of Multivariate Analysis 等统计杂志发表过多篇文章。