Main

derandomization

Computer science / Coursework / Randomized algorithms Lecture 1: Introduction Motivating examples (fingerprinting, Karger min-cut, QuickSort, Freivalds) where a few coin flips replace heavy deterministic work at a tiny, controllable error. Computer science / Coursework / Randomized algorithms Lecture 8: Derandomization Removing randomness while keeping the speed: enumeration, non-uniform advice, conditional probabilities with pessimistic estimators, k-wise independence, and PRGs (Nisan–Wigderson).