Topics 1 Approximation Algorithms Book Approximation Algorithms by

Topics 1. Approximation Algorithms: Book “Approximation Algorithms” by Vijay V. Vazirani, Chapter 3, Steiner Tree and TSP (Travelling Salesman Problem). 2. Randomized Algorithms: Book "Randomized Algorithms“ by Rajeev Motwani and Prabhakar Raghavan. Chapter 11, Section 11. 3, Approximating the Permanent. 3. Parallel and Distributed Algorithms: Book "Randomized Algorithms“ by Rajeev Motwani and Prabhakar Raghavan. Chapter 12, Section 12. 4 Perfect Matchings and Section 12. 6 Byzantine Agreement. 4. Convex Optimization: Book “Convex Optimization” by Stephen Boyd and Lieven Vandenberghe. Chapter 9, Unconstrained Minimization. Sections 9. 1, 9. 2 Descent Methods, 9. 3 Gradient Descent Method, 9. 4 Steepest Descent Method. 5. Streaming Algorithms: “Crash Course on Data Stream Algorithms, Part 1” by Andrew Mc. Gregor. Article in IVLE. 6. Machine Learning: “Online Algorithms in Machine Learning” by Avrim Blum. Article in IVLE.

Helpful things to remember • The key and most important point that is tested: Your understanding of the algorithms and analysis and clarity of your explanations. • Must do a run of the talk among the group members, a few days before the actual talk to the class. • • a) b) c) Helps in syncing notations, fonts etc. in slides of different members (they must be consistent). The group members must ask questions between themselves so that all aspects of algorithm and analysis are clarified. This has been very helpful in the last couple of years to all the groups to improve their presentations. Explain the key points of the algorithms first and then the other details. a) b) Ask yourself: What you would like to remember about the algorithm six months from now? Try to state it in a few sentences only. Must finish the presentation by 90 minutes. 30 minutes must be left for questions by the audience. Questions can be asked in between. a) b) We want to understand a few things but understand them well. (Not a lot of things that are unclear). A thumb rule: No more than three algorithms plus analysis. • Can use the slides and materials from the web, must give appropriate mention of the source. • Marking scheme : 40 marks for each presentation and 20 marks for IVLE forum discussions. • Information about previous years: www. comp. nus. edu. sg~rahul