Kullback-Leibler divergence

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Protected: Fundamentals of Stochastic Bandid Problems

Basics of stochastic bandid problems utilized in digital transformation, artificial intelligence, and machine learning tasks (large deviation principle and examples in Bernoulli distribution, Chernoff-Heffding inequality, Sanov's theorem, Heffding inequality, Kullback-Leibler divergence, probability mass function, hem probability, probability approximation by central limit theorem).
最適化:Optimization

Protected: Nonparametric Bayesian Point Processes and the Mathematics of Statistical Machine Learning Overview

An overview of the nonparametric Bayesian method, a probability generation model in infinite dimensions
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