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CS 531 — Parameterized Algorithms
(dt. Parametrisierte Algorithmen)

Level, degree of commitment Specialization module, compulsory elective module
Forms of teaching and learning,
workload
Lecture (3 SWS), recitation class (1 SWS),
180 hours (60 h attendance, 120 h private study)
Credit points,
formal requirements
6 CP
Course requirement(s): Successful completion of at least 50 percent of the points from the weekly exercises as well as at least 2 presentations of the tasks.
Examination type: Oral examination (individual examination) or written examination
Language,
Grading
English,
The grading is done with 0 to 15 points according to the examination regulations for the degree program M.Sc. Computer Science.
Duration,
frequency
One semester,
irregular
Person in charge of the module's outline Prof. Dr. Christian Komusiewicz

Contents

  • Parametrized and Exact Algorithms
  • Basic algorithmic techniques for parameterized algorithms: Search tree algorithms, tree decompositions, iterative compression, color coding.
  • Data reduction and kernelization
  • Advanced algorithmic techniques for parameterized algorithms, e.g. parameterization via lower bounds, inclusion-exclusion, representative sets
  • Parameterized complexity theory

Qualification Goals

Students will be able to

  • identify adequate parameterizations for hard computational problems,
  • develop efficient fixed-parameter algorithms and analyze their running time,
  • design data reduction rules and analyze their effectiveness, and
  • Demonstrate the algorithmic difficulty of parameterized computational problems.

Prerequisites

The following module is required: Algorithms and Data Structures. In addition, successful participation in the module „Effiziente Algorithmen“ (Efficient Algorithms) is recommended.


Applicability

Module imported from M.Sc. Computer Science.

It can be attended at FB12 in study program(s)

  • B.Sc. Data Science
  • B.Sc. Computer Science
  • M.Sc. Data Science
  • M.Sc. Computer Science

When studying B.Sc. Data Science, this module can be attended in the study area Free Compulsory Elective Modules.

The module is assigned to Computer Science. Further information on eligibility can be found in the description of the study area.


Recommended Reading

  • Cygan et al. Parameterized Algorithms. Springer Verlag, 2015.
  • Downey, Fellows: Fundamentals of Parameterized Complexity Theory. Springer Verlag 2013.
  • Niedermeier: Invitation to Fixed-Parameter Algorithms. Oxford University Press, 2006.
  • Flum, Grohe: Parameterized Complexity Theory. Springer Verlag, 2006.



Please note:

This page describes a module according to the latest valid module guide in Winter semester 2023/24. Most rules valid for a module are not covered by the examination regulations and can therefore be updated on a semesterly basis. The following versions are available in the online module guide:

  • Winter 2016/17 (no corresponding element)
  • Summer 2018 (no corresponding element)
  • Winter 2018/19 (no corresponding element)
  • Winter 2019/20 (no corresponding element)
  • Winter 2020/21 (no corresponding element)
  • Summer 2021 (no corresponding element)
  • Winter 2021/22 (no corresponding element)
  • Winter 2022/23 (no corresponding element)
  • Winter 2023/24

The module guide contains all modules, independent of the current event offer. Please compare the current course catalogue in Marvin.

The information in this online module guide was created automatically. Legally binding is only the information in the examination regulations (Prüfungsordnung). If you notice any discrepancies or errors, we would be grateful for any advice.