아래와 같이 초청특강을 개최하오니 관심있는 여러분의 많은참석 부탁드립니다.

1. 일시 : 2024년 8월 8일 (목), 오후 3시-

2. 장소 : 통계학과 스마트강의실 (자연대연구실험동 222호)

3. 연사 : 송호승 교수 (카이스트, 산업및시스템공학과)

4. 연제 : Practical and powerful kernel-based change-point detection

Abstract

Change-point analysis plays a significant role in various fields to reveal discrepancies in distribution in a sequence of observations. While a number of algorithms have been proposed for high-dimensional data, kernel-based methods have not been well explored due to difficulties in controlling false discoveries and mediocre performance. In this paper, we propose a new kernel-based framework that makes use of an important pattern of data in high dimensions to boost power. Analytic approximations to the significance of the new statistics are derived and fast tests based on the asymptotic results are proposed, offering easy off-the-shelf tools for large datasets. The new tests show superior performance for a wide range of alternatives when compared with other state-of-the-art methods. We illustrate these new approaches through an analysis of a phone-call network data. All proposed methods are implemented in an R package kerSeg.