学术报告
Functional Regression on Manifold with Contamination - 姚方教授 （多伦多大学、北京大学）
题目：Functional Regression on Manifold with Contamination
报告人：姚方教授 （多伦多大学、北京大学）
摘要：We propose a new perspective on functional regression with a predictor process via the concept of manifold that is intrinsically finite-dimensional and embedded in an infinite-dimensional functional space, where the predictor is contaminated with discrete/noisy measurements. By a novel method of functional local linear manifold smoothing, we achieve a polynomial rate of convergence that adapts to the intrinsic manifold dimension and the level of sampling/noise contamination with a phase transition phenomenon depending on their interplay. This is in contrast to the logarithmic convergence rate in the literature of functional nonparametric regression. We demonstrate that the proposed method enjoys favourable finite sample performance relative to commonly used methods via
simulated and real data examples.
时间：11月8 日（星期三）上午10:30--11:30
地点：首师大新教二楼813教室
欢迎全体师生积极参加！
