# 186.855 Fixed-Parameter Algorithms and Complexity This course is in all assigned curricula part of the STEOP.\$(function(){PrimeFaces.cw("Tooltip","widget_j_id_21",{id:"j_id_21",showEffect:"fade",hideEffect:"fade",target:"isAllSteop"});});This course is in at least 1 assigned curriculum part of the STEOP.\$(function(){PrimeFaces.cw("Tooltip","widget_j_id_23",{id:"j_id_23",showEffect:"fade",hideEffect:"fade",target:"isAnySteop"});}); 2021W 2020W 2019W 2018W 2017W 2016W 2015W

2021W, VU, 2.0h, 3.0EC, to be held in blocked form

## Properties

• Semester hours: 2.0
• Credits: 3.0
• Type: VU Lecture and Exercise
• Format: Online

## Learning outcomes

After successful completion of the course, students are able to understand the theory of parameterized complexity and fixed-parameter tractability in sufficient depth to read and follow latest developments in the area and, crucially, to analyze problems they encounter from the parameterized viewpoint. First and foremost, this includes the ability to obtain asymptotically efficient algorithms and strong lower bounds for problems of interest.

## Subject of course

Fixed-parameter algorithms provide a powerful approach for efficiently solving many NP-hard problems by exploiting structural aspects of problem instances in terms of a problem parameter. This course provides an overview of the main techniques for developing fixed-parameter algorithms (including bounded search trees, kernelization, color coding, modulators) as well as the fundamentals of parameterized complexity theory (such as the Weft-hierarchy, XP and para-NP-hardness, kernelization lower bounds) which allows to provide strong evidence that certain problems cannot be solved by a fixed-parameter algorithm.

## Teaching methods

The core of the course consists of a series of blocked lectures which explore advanced topics in the studied area. The lectures are held in an informal, seminar-like setting and are highly interactive - students are expected to actively engage in what's going on. Every new method and technique introduced during the lecture is demonstrated on several examples.

Written and oral

## Course dates

DayTimeDateLocationDescription
Mon13:00 - 16:3010.01.2022 - 24.01.2022 (LIVE)Zoom Lectures
Thu13:00 - 16:3013.01.2022 - 27.01.2022 (LIVE)Zoom Lectures
Fixed-Parameter Algorithms and Complexity - Single appointments
DayDateTimeLocationDescription
Mon10.01.202213:00 - 16:30 Zoom Lectures
Thu13.01.202213:00 - 16:30 Zoom Lectures
Mon17.01.202213:00 - 16:30 Zoom Lectures
Thu20.01.202213:00 - 16:30 Zoom Lectures
Mon24.01.202213:00 - 16:30 Zoom Lectures
Thu27.01.202213:00 - 16:30 Zoom Lectures
Course is held blocked

## Examination modalities

The grading is based on a two-step evaluation process. In the first and mandatory part, each student is expected to select a recent research paper (based on guidance from the lecturer) from the considered area, read it, and prepare a presentation of its contents. This is sufficient to pass the course with a basic grade. Students who want a good grade take an oral exam where they demonstrate their understanding of the topics covered in the lecture.

## Course registration

Begin End Deregistration end
01.09.2021 00:01 13.01.2022 23:59 13.01.2022 23:59

## Curricula

Study CodeObligationSemesterPrecon.Info
066 011 Double degree programme "Computational Logic (Erasmus-Mundus)" Mandatory elective
066 645 Data Science Mandatory elective
066 931 Logic and Computation Mandatory elective
066 937 Software Engineering & Internet Computing Mandatory elective
066 938 Computer Engineering Mandatory elective

## Literature

No lecture notes are available.

## Previous knowledge

This course requires basic knowledge on the design and analysis of algorithms as well as basic complexity theory. Knowledge of the topics covered in the Algorithmics course is an advantage.

English