报告名称：Advances in tensor complementarity problems

主讲人：黄正海 教授

邀请人：宋义生 教授

时间：2023年6月16日   15:00

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报告摘要

Tensor is an effective tool to describe large-scale complex data, which has been widely concerned and studied in the era of big data. Data in the real world usually has a special structure, so structure tensors have received a lot of research. As an application of structure tensors, a class of complementarity problem, called tensor complementarity problem, was proposed in 2015. Since then, many scholars have devoted themselves to the study of this problem. At present, the research of tensor complementarity has achieved fruitful results, including theoretical research, algorithm research and application research. In addition, some extended models of tensor complementarity problems have also been developed. This report will provide a systematic review of the developments in this field in order to promote the further development of this field.

专家简介

黄正海，天津大学数学学院教授、博士生导师。主要从事最优化理论、算法及其应用方面的研究工作，在求解互补与变分不等式问题、对称锥优化与对称锥互补问题、稀疏优化、张量优化、核磁共振医学成像、人脸识别等方面取得了一些有意义的成果。目前的主要研究兴趣是张量优化、特殊结构的变分不等式与互补问题、以及机器学习中的优化理论方法及其应用。已发表SCI检索论文120多篇，其中代表作发表于Mathematical Programming、SIAM Journal on Optimization、SIAM Journal on Matrix Analysis and Applications、SIAM Journal on Imaging Sciences、IEEE Transactions on Information Theory、IEEE Transactions on Information Forensics and Security等；连续获得多项国家自然科学基金资助。曾获得中科院优秀博士后奖和教育部高等学校自然科学奖二等奖。目前为中国运筹学会常务理事，中国运筹学会数学规划分会副理事长；国际期刊《Pacific Journal of Optimization》、《Asia-Pacific Journal of Operations Research》、《Applied Mathematics and Computation》和《Optimization,Statistics & Information Computing》的编委、中国核心期刊《运筹学学报》的编委。