报告名称：Sparse Representation based Classification: A Theoretical Perspective

主办单位：英国立博官网中文版

报告专家：王玉龙

专家所在单位：成都大学

报告时间：2018年12月12日10：00-12：00

报告地点：英国立博官网中文版203报告厅

专家简介：王玉龙，澳门大学博士，成都大学特聘副研究员，主要从事模式识别与机器学习研究。近五年，在相关领域已发表19篇SCI期刊论文和10余篇EI会议论文，包括10篇IEEE Transactions论文，以第一作者发表论文于国际权威期刊IEEE TPAMI（为2019年该期刊首篇论文）, TIP, TSP, TCYB, PR等。作为项目负责人主持国家自然科学基金青年项目。

报告摘要：Representation-based classification (RC) methods such as sparse RC (SRC) have attracted great interest in pattern recognition, computer vision and remote sensing in recent years. Despite their empirical success, few theoretical results have been reported to justify their effectiveness. Establishing theoretical guarantees for RC methods can help us have a better understanding of when and why they can succeed in classification. This talk will introduce the algorithm, theory and applications of SRC, with an emphasis on the recent theoretical results.