BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Department of Mathematics - ECPv5.7.0//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Department of Mathematics
X-ORIGINAL-URL:https://math.sciences.ncsu.edu
X-WR-CALDESC:Events for Department of Mathematics
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20210314T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20211107T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210115T120000
DTEND;TZID=America/New_York:20210115T130000
DTSTAMP:20210613T154047
CREATED:20210106T161606Z
LAST-MODIFIED:20210108T173453Z
UID:18720-1610712000-1610715600@math.sciences.ncsu.edu
SUMMARY:Diego Cifuentes\, MIT\, Advancing scalable\, provable optimization methods in semidefinite & polynomial programs
DESCRIPTION:Optimization is a broad area with ramifications in many disciplines\, including machine learning\, control theory\, signal processing\, robotics\, computer vision\, power systems\, and quantum information. I will talk about some novel algorithmic and theoretical results in two broad classes of optimization problems. The first class of problems are semidefinite programs (SDP). I will present the first polynomial time guarantees for the Burer-Monteiro method\, which is widely used for solving large scale SDPs. I will also discuss some general guarantees on the quality of SDP solutions for parameter estimation problems. The second class of problems I will consider are polynomial systems. I will introduce a novel technique for solving polynomial systems that\, by taking advantage of graphical structure\, is able to outperform existing techniques by orders of magnitude. \nZoom Link: https://ncsu.zoom.us/j/92555512643?pwd=c3pJeCtOSEg3LzEwZU9WK0kwWVdjZz09 \nWebsite: http://www.mit.edu/~diegcif/
URL:https://math.sciences.ncsu.edu/event/diego-cifuentes/
LOCATION:Zoom
CATEGORIES:Special Seminar
END:VEVENT
END:VCALENDAR