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CS6234 Advanced Algorithm Design Course Overview

Dive into advanced algorithm design in this seminar-based course. Develop research skills tackling algorithmic problems independently. Course covers topics like graph matching, linear programming, and approximation algorithms. Explore textbooks by Kleinberg & Tardos, Papadimitriou & Steiglitz, and more. Emphasizes independent research and academic integrity. Engage in student presentations and projects. Prerequisites: CS5206. Course website: http://www.comp.nus.edu.sg/~CS6234/2009/

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CS6234 Advanced Algorithm Design Course Overview

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  1. CS6234: Spring 2009 (Overview) CS6234: Advanced Algorithms • Instructors: • Leong Hon Wai, COM1 03-41 • Panagiotis Karras, COM1 02-18 • Course webpage • http://www.comp.nus.edu.sg/~CS6234/2009/ • Course Objectives: • Advanced treatment of algorithm design • Seminar based course (you give lecture too) • Independent research on an algorithmic problem

  2. CS6234: Overview (2) • Course Assessment: • 20% Midterm • 30% Reading and Presentation • 50% Research Project • Target Students: • Research students • Those aiming to do research in algorithm design

  3. CS6234: Overview…(3) • Pre-requisite: • CS5206 or the old CS5234 • Textbook: No single textbook, but… • Reference Material: • [PS82] Combinatorial Optimization: Algorithm & Complexity, by Papadimitriou and Steiglitz, Prentice-Hall, 1982. • [KT06] Algorithm Design, by Kleinberg & Tardos Addison-Wesley, 2006. • [CLRS01] Introduction to Algorithms, (2nd edition) by Cormen, Leiserson, Rivest, Stein, MIT Press, 2001. • [Schr03] Combinatorial Optimization: Polyhedral and Efficiency, by A. Schrijver, Springer, 2003.

  4. CS6234: Tentative Schedule • Week 1: Course Intro and Graph Matching • Week 2: Linear Programming • Week 3: Approximation Algorithms • Week 4: Online Algorithms • Week 5: Randomized Algorithms • Week 6: Special Topics in Data Engineering • Week B: BREAK • Week 7: Mid-Term • Week 8: Student Lectures • Week 9: Student Lectures mm • Week 10: Student Lectures / Special Topic • Week 11: Student Lectures / Special Topic • Week 12: Course Summary and Review • Week 13: Student Project Poster Presentations

  5. We will not cover • Data Structures • Trees, Priority-Queues, etc • Basic algorithm design paradigms • Divide-and-Conquer, Greedy, DP, Std Graph Alg, • Amortized complexity • Basic NP-Completeness • NP, reduction, NP-Completeness proofs Take CS5206 instead!

  6. About class organization… • (adapted from similar slides by OoiWT)

  7. Philosophy • Students are expected to be • Mature • Independent • Resourceful • What you learn is (should be) more important than your grade

  8. Please don’t ask … • “Is this equation important?” • “Is this equation examinable?” • “Do I have to memorize this algorithm?”

  9. Please do ask … • “What is the effect of changing k in the equation?” • “Why did the author define this quantity in his algorithm?” • “Is there another way of computing this quantity?” • “Can this algorithm be applied to other problems that I have seen before?”

  10. Academic Honesty • No copying among students • No copying from published work ZERO TOLERENCE to Plagiarism

  11. Discussion? • Strongly encouraged … • but • must acknowledge all contributions • write up solutions independently

  12. Thankyou. Q & A

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