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Course CS 7800 Advanced Algorithms
Semester Spring 2025
Instructor Soheil Behnezhad
(Office hours: Tuesdays 3:30pm-4:30pm at WVH 348.)
Meeting Time Tuesdays and Fridays 9:50am - 11:30am in Snell Library 049
Office Hours Tuesdays 3:30pm-4:30pm
TA Amir Azarmehr
(Office hours: TBD)
Prerequisites

This is a rapid course covering advanced algorithms. It is intended primarily for PhD students in Khoury, but if you are not one, you need the instructor's permission to enroll. You will be well-prepared for this course if you have completed an undergraduate algorithms course (e.g. CS3000) and are comfortable in mathematical reasoning and communication. The ability to reason mathematically is more important than prior knowledge.

Given that this is a PhD-level course, participants may have varying backgrounds, and you might need to address some gaps in your knowledge yourself. If you have any concerns about your background, I encourage you to discuss them with me during the first week of classes.

Course Overview
We will cover the (mathematical) foundations of algorithms. We will review some material covered in CS5800/CS3000 and then cover more advanced algorithms.

Grading
  • 20% Midterm 1
  • 20% Midterm 2
  • 30% Final Exam
  • 30% Homework Assignments (5 HWs)
  • +5% Active Participation

Schedule
# WD Date Topics References Notes
Tu 1/7 Introduction + Stable Matching slides
Fr 1/10 Greedy Algorithms
Tu 1/14 No Class
Fr 1/17 Greedy Algorithms
Tu 1/21 Dynamic Programming
Fr 1/24 Dynamic Programming
Tu 1/28 Graph Algorithms
Fr 1/31 Maximum Flow
Tu 2/4 Maximum Flow
Fr 2/7 Maximum Flow Applications
Tu 2/11 Maximum Flow Applications
Fr 2/14 Midterm 1
Tu 2/18 Linear Programming
Fr 2/21 Linear Programming
Tu 2/25 Multiplicative Weights
Fr 2/28 Multiplicative Weights
Tu 3/4 Intractability
Fr 3/7 Intractability
Tu 3/11 Spring Break
Fr 3/14 Spring Break
Tu 3/18 Randomization in Algorithms
Fr 3/21 Randomization in Algorithms
Tu 3/25 Randomization in Algorithms
Fr 3/28 Randomization in Algorithms
Tu 4/1 Midterm 2
Fr 4/4 Approximation Algorithms
Tu 4/8 Approximation Algorithms
Fr 4/11 Sublinear Algorithms
Tu 4/15 Sublinear Algorithms
Fr 4/18 Sublinear Algorithms
Tu 4/22 Final Exam
Resources

There is no official textbook that includes all the material of this class. The following, however, is a list of helpful supplementary resources.

  • Useful textbooks
  • Randomized algorithms
  • Useful books/surveys on sublinear algorithms