Credits: 5

Schedule: 07.01.2020 - 02.04.2020

Teaching Period (valid 01.08.2018-31.07.2020): 

III - IV (Spring)

Learning Outcomes (valid 01.08.2018-31.07.2020): 

This course will deepen your knowledge and skills in algorithm design. You will become familiar with a number of advanced design principles and tradeoffs between quantities such as running time, space usage, parallel speedup, success probability, and quality of approximation.

Content (valid 01.08.2018-31.07.2020): 

Advanced algorithm design techniques such as randomization, approximation, parameterisation, and algebrisation. Examples of contemporary advanced algorithms and supporting data structures. Tradeoffs between objectives and computational resources. The course consists of a fixed core part and a varying part covering topics of current interest.

Assessment Methods and Criteria (valid 01.08.2018-31.07.2020): 

Points earned from weekly problem sets determine the course grade.

Workload (valid 01.08.2018-31.07.2020): 

Lectures. Teaching in small groups. Independent work.

Study Material (valid 01.08.2018-31.07.2020): 

Lecture notes and articles.

Substitutes for Courses (valid 01.08.2018-31.07.2020): 

Replaces former courses T-79.5207 Advanced Course in Algorithms, T-79.5201 Discrete Structures, T-79.5202 Combinatorial Algorithms, and T-79.5203 Graph Theory.

Prerequisites (valid 01.08.2018-31.07.2020): 

Fundamentals of algorithm design and analysis. Mathematics studies in Bachelor's degree. 

Grading Scale (valid 01.08.2018-31.07.2020): 



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