应学院邀请，对外经济贸易大学统计学院熊巍教授将在线作学术报告。
报告题目：Mode-Based Classifier: A Robust and Flexible Discriminant Analysis for High-Dimensional Data
报告摘要：High-dimensional classification is both challenging and of interest in numerous applications. Componentwise distance-based classifiers, which utilize partial information with known categories, such as mean, median and quantiles, provide a convenient way. However, when the input features are heavy-tailed or contain outliers, performance of the centroid classifier can be poor. Beyond that, it frequently occurs that a population consists of two or more subpopulations, the mean, median and quantiles in this scenario fail to capture such a structure that can be instead preserved by mode, which is an appealing measure of considerable significance but might be neglected. We introduce and investigate componentwise mode-based classifiers that can reveal important structures missed by existing distance-based classifiers. We explore several strategies for defining the family of mode-based classifiers, including the unimodal classifiers, the multimodal classifier and the quantile-mode classifier. We establish the asymptotic properties of these methods and demonstrate through simulation studies and three real datasets that the mode-based classifiers compare favorably to the current state-of-art methods.
报告时间：2024年10月25日(周五)上午10:00
报告地点：腾讯会议号 289-329-880
邀 请 人：田玉柱副教授 张建东副教授
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报告人简介:
熊巍，对外经济贸易大学统计学院教授，博士生导师，数据科学系系主任兼党支部书记，惠园优秀青年学者。主要从事复杂高维数据分析、统计建模与机器学习等方面的研究。在Annals of Statistics，Statistica Sinica，Journal of the Royal Statistical Society: Series A， Statistics in Medicine，《中国科学：数学》、《统计研究》等国际国内重要刊物发表论文30余篇。主持国家自然科学基金和教育部人文社科项目多项。主讲数理统计、现代统计学，数据科学理论与实践等课程。曾荣获首届中国高校财经慕课联盟“同课异构”课程思政教学竞赛一等奖，获得校级优秀研究生指导教师、优秀系主任、优秀班主任、科研标兵等荣誉称号。
甘肃省数学与统计学基础学科研究中心
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2024年10月16日
