Topics will vary from semester to semester. See Computer Science Division announcements.

Course Description: Error-correcting codes play an important role in many areas of science and engineering, as they safeguard the integrity of data against the adverse effects of noise in communication and storage. They have also become important tools in the theory of computing and discrete mathematics.Starting with a fast-paced review of the basics of coding theory and some of the classic theorems (and challenges) of the subject, the course will move to a subset of several modern (still actively researched) topics in code constructions and error-correction algorithms. Possible topics include algebraic codes and decoding algorithms; polar codes for achieving Shannon capacity; list decoding for optimal recovery against worst-case errors; locally decodable and repairable codes to correct errors very efficiently; graph based codes and efficient iterative decoders; locally testable codes; quantum error-correcting codes; connections between coding theory and pseudorandomness; codes for combating synchronization errors; coding for interactive communication, etc. The goal is to expose students to some of the exciting frontiers and recent developments in the field, and in order to accomplish this goal within the allotted lecture time, students will be expected to do readings that supplement the lectures, especially in the beginning to get a good grounding on the basics of coding theory. This is a theoretically oriented graduate course targeted at EECS and Math PhD students, though mathematically sophisticated undergraduates should also find the course stimulating and may take the course with instructor permission.

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