Research Seminar StaGe: Statistics, Geometry and their interaction with Graph Theory

2020/2021
Academic Year
ENG
Instruction in English
5
ECTS credits
Type:
Elective course
When:
2 year, 1 semester

Instructors

Course Syllabus

Abstract

The course takes place every other week (once every two weeks) and each session lasts 2 academic hours. Sessions alternate between presentations by invited researchers and topical lectures on subjects ranging from Comparison Geometry and Optimal Transport to Graph Theory with a clear inclination towards questions of statistical nature.
Learning Objectives

Learning Objectives

  • To provide doctoral students with theoretical background and exposure to current research topics presented by invited leading researchers, academic members of the computer science faculty or students themselves.
Expected Learning Outcomes

Expected Learning Outcomes

  • Solve mathematically challenging problems.
  • Work in group environment.
  • Read, write and present research in mathematics and theoretical computer science.
Course Contents

Course Contents

  • Geometry, Graph Theory, Probability and Statistics.
Assessment Elements

Assessment Elements

  • non-blocking Presentation
  • non-blocking Attendance
  • non-blocking Presentation
  • non-blocking Attendance
Interim Assessment

Interim Assessment

  • Interim assessment (1 semester)
    0.5 * Attendance + 0.5 * Presentation
Bibliography

Bibliography

Recommended Core Bibliography

  • Cesa-Bianchi, N., Lugosi, G. Prediction, learning, and games. – Cambridge university press, 2006. – 408 pp.

Recommended Additional Bibliography

  • Diestel R. Graph Theory. – Springer, 2017. – 428 pp.