报告名称:Atomic Representation based Classification: Theory, Algorithm and Applications
时间和地点:
2021年12月7日15:30-16:30
计算机楼313报告厅
报告摘要:Representation-based classification (RC) methods such as sparse RC have attracted intensive interest in pattern recognition and computer vision in recent years. In this talk, we will introduce a general and unified framework termed as ARC (Atomic Representation based Classification) for high-dimensional data analysis. In addition, we will also discuss the unified algorithm, theoretical guarantees and various applications of ARC, such as robust face recognition and handwritten digit recognition.
个人介绍:
华中农业大学信息学院教授,博士生导师。曾任新加坡南洋理工大学研究员,博士毕业于澳门大学。目前主持国家自然科学基金面上项目和青年项目各一项。在人工智能相关领域已发表20余篇SCI期刊论文和10余篇EI会议论文,其中包括13篇国际权威期刊IEEE汇刊(IEEE Transactions)论文,如IEEE TPAMI, TIP和TSP等。