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Lecture
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
This lecture covers the topics of Brun's Sieve, Martingales, and Conditional Expectations. It discusses the concepts of martingales with respect to random variables, the law of total expectation, and the function of support. The lecture also delves into Chernoff, Azuma, and Hoeffding inequalities, providing proofs and explanations. The instructor explores the relationship between martingales and conditional expectations, emphasizing the importance of understanding these concepts in probability theory.