报告题目：An exact penalty approach for optimization with nonnegative orthogonality constraints
报 告 人：姜波 副教授 南京师范大学
报告时间：2021年01月04日 上午 9:40-10:20
报告地点：腾讯会议 ID：320 247 940
会议密码：9999
校内联系人：李欣欣 xinxinli@jlu.edu.cn
报告摘要：Optimization with nonnegative orthogonality constraints has wide applications in machine learning and data sciences. It is NP-hard due to some combinatorial properties of the constraints. In this talk, we shall discuss an exact penalty approach for solving the considered problems. The penalty model can recover the solution if the penalty parameter is sufficiently large other than going to infinity. We establish the convergence of the penalty method under some weak and standard assumptions Extensive numerical results on the orthogonal nonnegative matrix factorization problem and the K-indicators model show the effectiveness of our proposed approaches.
报告人简介：姜波，南京师范大学数学科学学院副教授、硕士生导师、中国运筹学会数学规划分会的青年理事。入选第三届中国科协“青年人才托举工程”。主要研究方向为非线性优化算法与理论，特别是带有正交约束的优化问题及其应用，已在Mathematical Programming, SIAM Journal on Optimization, SIAM Journal on Scientific Computing, IEEE Transactions on Image Processing等优化和信息类顶级期刊发表论文7篇。目前主持国家自然科学基金面上项目1项，曾主持国家自然科学基金青年项目1项、江苏省青年基金项目1项。
