报告人： 矫立国博士

报告时间：2019年3月21日(周四) 上午 09：00-11:30

报告地点：精正楼二楼学术报告厅

Abstract. We review several (and provide new) results on the theory of moments, sums of

squares, and basic semialgebraic sets when convexity is present. In particular, we show that, under

convexity, the hierarchy of semidefinite relaxations for polynomial optimization simplifies and has

finite convergence, a highly desirable feature as convex problems are in principle easier to solve.