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The main goal of this course is to study the generalization ability of a number of popular machine learning algorithms such as boosting, support vector machines and neural networks. Topics include Vapnik-Chervonenkis theory, ...

Laws of large numbers and central limit theorems for sums of independent random variables, conditioning and martingales, Brownian motion and elements of diffusion theory.

Laws of large numbers and central limit theorems for sums of independent random variables, conditioning and martingales, Brownian motion and elements of diffusion theory.