PROBABILISTIC TOOLKIT FOR LEARNING AND COMPUTING

Credit Hours: 3 · Graduate

Randomness is one of the strongest tools which enables designing efficient algorithms. The applications of randomness in computer science spans machine learning algorithm, cryptography, networks, distributed systems. In this course, we study a variety of probabilistic tools and techniques that allow us to harness the power of randomness and apply it in algorithm design and learning theory. Recommended Prerequisite(s): COMP 382