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X-WR-CALNAME;VALUE=TEXT:Eventi DIAG
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UID:calendar.31568.field_data.0@www.diag.uniroma1.it
DTSTAMP:20261014T032652Z
CREATED:20261006T094309Z
DESCRIPTION:Prof. Wiegele will teach the following 10 hours PhD course Bio:
   Angelika Wiegele is a mathematician working on semidefinite optimization
  and combinatorial optimization. She is Professor at the Mathematics Depar
 tment at Alpen-Adria-Universität Klagenfurt. Angelika studied mathematics 
 in Klagenfurt\, London\, and Eindhoven. She earned her master in mathemati
 cs (2001) and her Ph.D. in mathematics (2006) at Alpen-Adria-Universität K
 lagenfurt. She held research and/or teaching positions in Graz (Department
  of Mathematics)\, Klagenfurt (Department of Mathematics)\, Rome (IASI-CNR
 ) and Cologne (Institut f. Informatik). She was visiting professor at the 
 Università degli Studi di Roma 'Tor Vergata'\, Department of Civil  Engine
 ering and Computer Science Engineering in fall 2019. In the years 2022 unt
 il 2024 she was member of the Global Faculty of the University of Cologne.
  Her research bridges theory and practical computation\, and she has publi
 shed extensively in optimization journals. She has also successfully acqui
 red third-party funded projects\, most notably as the coordinator of the M
 SCA doctoral network ALMOA\, a Marie Skłodowska-Curie Actions network that
  trains doctoral researchers in optimization. Abstract: Semidefinite progr
 amming (SDP) extends linear programming to optimization over the cone of p
 ositive semidefinite matrices\, and it has become a central tool for obtai
 ning strong relaxations of hard combinatorial problems. This course offers
  a compact introduction to the theory\, the algorithms\, and the applicati
 ons of SDP. We begin with the necessary background in linear algebra\, con
 vex sets\, and positive semidefinite matrices\, and then develop the found
 ations of semidefinite programming\, including duality theory. The algorit
 hmic part of the course covers two complementary approaches: interior poin
 t methods\, which deliver high-accuracy solutions for small to medium-size
 d problems\, and alternating direction methods\, which scale to much large
 r instances at lower accuracy. The course concludes by showing how classic
 al combinatorial optimization problems can be modeled as integer semidefin
 ite programs and how their semidefinite relaxations yield strong bounds. T
 he course is aimed at students and researchers in mathematics\, computer s
 cience\, and operations research who have a basic background in linear alg
 ebra and optimization.Il Corso si svolgerà presso il DIAG in Aula B203 e A
 ula A4 a via Ariosto 25\, 2 piano lato destro.   WhenWhat   Lecture 110/11
 /20269:00-11:00 Preliminaries: Linear Algebra\, Convex Sets and PositiveSe
 midefinite Matrices Room B203   Lecture 212/11/20269:00-11:00 Semidefinite
  Programming\, Duality Room B203   Lecture 313/11/20269:00-11:00 Interior 
 Point Methods Applied for Solving Semidefinite Programs Room A4Lecture 417
 /11/20269:00-11:00 Alternating Direction Methods for Solving SemidefiniteP
 rogramming Room B203Lecture 519/11/20269:00-11:00 Combinatorial Optimizati
 on Problems modeled as IntegerSemidefinite Programming Problems Room A4 
DTSTART;TZID=Europe/Paris:20261110T090000
DTEND;TZID=Europe/Paris:20261119T110000
LAST-MODIFIED:20261006T095836Z
LOCATION:Aula B203 e A4 DIAG
SUMMARY:Semidefinite Programming: Theory\, Algorithms and Applications in C
 ombinatorial Optimization - Prof. Angelika Wiegele
URL;TYPE=URI:https://www.diag.uniroma1.it/node/31568
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