Lee. Randomized Algorithms and Probabilistic Analysis. Washington.
Topics include Discrete probability, High-dimensional geometry and statistics, Information and entropy, and Markov chains and convergence to equilibrium.
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- 2026-10-10
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Mary Wootters. Randomized Algorithms and Probabilistic Analysis. Stanford web.stanford.edu
Key tools of probabilistic analysis, and application of these tools to understand the behaviors of random processes and algorithms. Emphasis is on theoretical foundations, though applications will be discussed in machine learning and data analysis, networking, and systems…
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Theoretical Computer Science › Randomization & Probability > Lecture Notes: “Topics include Discrete probability, High-dimensional geometry and statistics, Information and entropy, and Markov chains and convergence to equilibrium.”