Randomized-Algorithms

• The Probabilistic Method and Randomized Algorithms: From Tail Bounds to Derandomization · 2025-05-30

  Master the probabilistic method — Paul Erdős's beautiful technique for proving existence non-constructively — alongside the tail bounds (Chernoff, Hoeffding, Azuma) that make randomized algorithms practical, and the modern methods for removing randomness.

• Markov Chains for Computer Science: MCMC, Mixing Times, and Randomized Algorithms · 2022-01-31

  A rigorous treatment of Markov chains from a computer science perspective—Metropolis-Hastings, coupling bounds, spectral gaps, and the role of rapid mixing in modern randomized algorithms.