CSCE 52803 Graph and Combinatorial Algorithms

Fall 2026 Course Syllabus

JBHT Rm 0239, MoWeFr 10:45AM - 11:35AM

Schedule Assignments

Instructor Dr. Lu Zhang

Office JBHT 522, (479)575-4382

Email lz006 at uark dot edu

URL http://csce.uark.edu/~lz006/

Office Hours MoWe 2:00 - 3:00 PM, JBHT 522

Course Description

Introduction to graph and combinatorial optimization problems, P and NP problems, approximation algorithms for solving NP hard problems and machine learning approaches for solving NP hard problems.

Course Material

Guichard, D. (2017). An introduction to combinatorics and graph theory. Whitman College-Creative Commons.

Vazirani, V. V. (2001). Approximation algorithms (Vol. 1). Berlin: springer.

L. Wu, P. Cui, J. Pei, and L. Zhao. (2022). Graph Neural Networks: Foundations, Frontiers, and Applications. Springer, Singapore. Available online: https://graph-neural-networks.github.io/index.html

Dive into Deep Learning, by Aston Zhang and Zachary C. Lipton and Mu Li and Alexander J. Smola (2020). Available online: https://d2l.ai/

Richard S. Sutton and Andrew G. Barto (2018). Reinforcement learning: An introduction. A Bradford Book, Cambridge, MA, USA.

Grading

Assignment 45%, Presentation 25%, Final Exam 30%.

Topics Covered

- Introduction and preliminaries

- Tractable graph problems

- P and NP

- Approximation algorithms

- Intractable graph problems

- Machine learning fundamentals

- Graph neural networks

- Deep reinforcement learning

- Learning augmented algorithms

- Machine learning for graph problems

- Paper reading and discussions

Course Syllabus