CSCI 421 - Computer Science Theory Topics Seminar

This course is an exploration of research in an area of theoretical computer science. Topics vary by offering. Example topics include randomized or parallel algorithms, approximation algorithms, quantum computation or complexity, and zero-knowledge proof systems. Not all topics offered every year.

Communication Complexity

An introduction to communication complexity, which studies how much data needs to be shared between a group of parties in order to solve a given problem. Unlike time and space complexity, communication complexity allows more negative bounds and precise characterizations. This class will emphasize not just the material but the learning process, with students building skills in independent learning and technical communication.

Unit(s): 0.5
Group Distribution Requirement(s): Distribution Group III
Prerequisite(s): Communication Complexity: MATH 113 and MATH 201
Instructional Method: Lecture-conference
Grading Mode: Letter grading (A-F)
Repeatable for Credit: May be taken 4 times for credit
Cross-listing(s): MATH 421
Group Distribution Learning Outcome(s):

Use and evaluate quantitative data or modeling, or use logical/mathematical reasoning to evaluate, test or prove statements.
Given a problem or question, formulate a hypothesis or conjecture, and design an experiment, collect data, or use mathematical reasoning to test or validate it.