Introduction to Css 413 1 Pseudorandomness Lecture 11
Let's dive into the details surrounding Css 413 1 Pseudorandomness Lecture 11. Instructor: Ramprasad Saptharishi Agenda: [Constructing expanders from scratch] Graph operations (squaring, tensoring), the ...
Css 413 1 Pseudorandomness Lecture 11 Comprehensive Overview
Instructor: Ramprasad Saptharishi Agenda: Introduction to the course, administrivia, general notion of Instructor: Prahladh Harsha Agenda: Randomness elimination/reduction via enumeration, method of conditional expectations and ... Instructor: Prahladh Harsha Introduction, Administrivia, The Power of Randomness, Is Randomness Essential? Can Randomness ...
Instructor: Prahladh Harsha Agenda: Randomized Complexity classes, Error Reduction, Basic Probability Inequalities, Sampling.
Summary & Highlights for Css 413 1 Pseudorandomness Lecture 11
- Instructor: Prahladh Harsha Agenda: vertex expansion, random graphs are vertex expanders, KPS error-reduction for RP.
- Instructor: Ramprasad Saptharishi Agenda: [
- Instructor: Prahladh Harsha Agenda: [Spectral expanders for sampling] Hitting set property for expander random walks, matrix ...
- Instructor: Prahladh Harsha Agenda: [The Saks-Zhou theorem] BPL is in DSPACE((log n)^{1.5})
- Instructor: Prahladh Harsha Agenda: Samplers,
That wraps up our extensive overview of Css 413 1 Pseudorandomness Lecture 11.
