Generalizations of Some Concentration Inequalities
Abstract
For a real-valued measurable function f and a nonnegative, nondecreasing function φ, we first obtain a Chebyshev type inequality which provides an upper bound for φ(λ1) μ(\x ∈ : f(x) ≥ λ1 \) + Σk=2n(φ(λk)- φ(λk-1)) μ(\x ∈ : f(x) ≥ λk\) , where 0 < λ1 < λ2 ·s λn < ∞. Using this, generalizations of a few concentration inequalities such as Markov, reverse Markov, Bienaym\'e-Chebyshev, Cantelli and Hoeffding inequalities are obtained.
0
Turn this paper into a lesson
ArcXiv compiles a structured reading guide from this paper's metadata: plain-English importance, contributions, prerequisite concepts, which sections to read first, flashcards, and a quiz. Grounded in the abstract, never invented.