2000 character limit reached
On Concentration Inequalities for Vector-Valued Lipschitz Functions
Published 28 Feb 2021 in math.PR | (2103.00651v1)
Abstract: We derive two upper bounds for the probability of deviation of a vector-valued Lipschitz function of a collection of random variables from its expected value. The resulting upper bounds can be tighter than bounds obtained by a direct application of a classical theorem due to Bobkov and G\"{o}tze.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.