This course covers a large spectrum of algorithmic topics such as approximation algorithms, randomized algorithms, parallel/distributed algorithms, and online algorithms. Students will learn how to analyze the most fundamental algorithms in these areas using various techniques from graph theory, probability theory, and algebra. After successful completion of the course, students will be able to design efficient and effective algorithms for similar problems leveraging these techniques. Furthermore, students will learn about the most recent research advancements in these areas by studying current research publications.
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Requisite and Incompatibility
To enrol in this course, you must have completed COMP6466 or COMP3600. Incompatible with COMP4600.
Referenced entries (3)
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- COMP6466 · 2027
- COMP3600 · 2027 · saved source not linked
- COMP4600 · 2027 · saved source not linked
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
Display a deep understanding of classical approximation and graph algorithms and their analysis.
Analyse the efficiency and correctness of randomized algorithms and data structures.
Demonstrate a good knowledge of parallel, distributed, and online algorithms.
Design and analyse efficient algorithms using various advanced algorithmic techniques such as linear programming, graph theory, probability theory, and algebra.
Understand, analyse, summarize, and present research publications in the area of algorithm design.
Published offerings
The page explicitly says there are no current offerings. This does not establish permanent discontinuation.
Complete offering text
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage. There are no current offerings for this course.
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assets/Courses/Computational Foundations/8000/Advanced Algorithms/Advanced Algorithms - ANU.html
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