Techniques for the design and analysis of randomized algorithms; discrete probability theory; randomized data structures; lower bound techniques; randomized complexity classes; advanced algorithmic applications from various areas.
This course may not be repeated for credit.
Notes
- Mathematics 321 or Statistics 321 is recommended as preparation for this course.
Antirequisite(s)
- Credit for Computer Science 522 and Computer Science 622 will not be allowed.
Sections
This course will be offered next in
Fall 2020.