2022 Fall Course

2. Course Objectives

Algorithms are procedures or methods that solve problems arising across the full range of computing applications. Algorithmic problems from those areas, however, are rarely mathematically well-formed and they often come with application-specific details, most of which are extraneous. The goal of this course is to understand how to formulate problems, and from this, how to design efficient algorithms for the resulting problems. The course starts with an introduction to algorithms. Then we study four essential algorithm design techniques: greedy algorithms, divide and conquer, dynamic programming, and network flow. We will also spend a few weeks on computational intractability and approximation algorithm, a technique for dealing with computational intractable problems.

3. Prerequisites & require

CSED101 Programming and Problem Solving
CSED233 Data structure

4. Grading

Midterm exam : 30%, Final exam : 30%, Homework : 20%,
Problem solving (programming, project) : 20%

5. Course Materials

Algorithms by Sanjoy Dasgupta, Christos Papadimitriou, and Umesh Vazirani, 2008, McGraw-Hill International Edition.

6. Course References

Algorithm Design by Jon Kleinberg and Éva Tardos, 2006, Addison Wesley.

7. Course Plan

# Week 1 : Introduction / Computational efficiency
# Week 2 : Recursion
# Week 3-4 : Backtracking
# Week 5-6 : Dynamic programming
# Week 7 : Greedy algorithms
# Week 8 : Midterm exam.
# Week 9-10 : Graph algorithms
# Week 11 : Maximum flows and Minimum cuts
# Week 12-13 : Computational intractability
# Week 14 : Local search heuristics
# Week 15 : Approximation algorithms / Randomized algorithms
# Week 16 : Final exam.

8. Course Operation

Lecture
Programming Assignment
Hand writing HW