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Learn Stein's method for diffusion approximations in queueing theory through this comprehensive tutorial lecture delivered by Prof. Anton Braverman from Northwestern University. Explore the generator comparison approach of Stein's method, a powerful framework for comparing stationary distributions of Markov processes and deriving bounds on their distance under integral probability metrics without requiring coupling of distributions. Discover how this approach has been successfully applied in queueing theory over the past decade to enhance understanding of diffusion approximations. Gain insights into stochastic modeling and applied probability techniques that have practical applications in domains such as ridesharing services and revenue management. Master the theoretical foundations and practical applications of this advanced mathematical framework through expert instruction from a leading researcher in operations research and applied probability.
