Understanding Css 413 1 Pseudorandomness Lecture 1
If you are looking for information about Css 413 1 Pseudorandomness Lecture 1, you have come to the right place. Instructor: Prahladh Harsha Introduction, Administrivia, The Power of Randomness, Is Randomness Essential? Can Randomness ...
Key Takeaways about Css 413 1 Pseudorandomness Lecture 1
- Instructor: Prahladh Harsha Agenda: Randomized Complexity classes, Error Reduction, Basic Probability Inequalities, Sampling.
- Instructor: Prahladh Harsha Agenda: vertex expansion, random graphs are vertex expanders, KPS error-reduction for RP.
- Instructor: Ramprasad Saptharishi Agenda: [Introduction to expansion] Vertex expansion, spectral expansion, connection between ...
- Instructor: Prahladh Harsha Finite fields, polynomial identity testing, Schwartz-Zippel Lemma, perfect matching in bipartite graphs.
- Instructor: Ramprasad Saptharishi Agenda: [Limited independence] Constructing k-wise independent families of hash functions, ...
Detailed Analysis of Css 413 1 Pseudorandomness Lecture 1
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: Ramprasad Saptharishi Agenda: [Basic derandomisation methods] Enumeration, method of conditional expectation, ...
Instructor: Prahladh Harsha Agenda: Samplers,
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