Concentration Inequalities for Bounded Random Vectors
arXiv:1309.0003v17 citations
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This work provides theoretical tools for analyzing multivariate bounded random variables, which is incremental as it extends existing scalar results to the vector case.
The paper tackles the problem of deriving concentration inequalities for bounded random vectors, generalizing Hoeffding's inequalities from scalars to vectors, and applies these results to obtain specific inequalities for multinomial and Dirichlet distributions.
We derive simple concentration inequalities for bounded random vectors, which generalize Hoeffding's inequalities for bounded scalar random variables. As applications, we apply the general results to multinomial and Dirichlet distributions to obtain multivariate concentration inequalities.