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math.ST2026

Bentkus-type asymptotic e-values

Diego Martinez-Taboada, Ben Chugg, Aaditya Ramdas

Asymptotic e-values are emerging as a powerful alternative to asymptotic p-values, particularly in post-hoc inference and multiple testing, where significance levels may be data-de…

math.ST2026

Sharp Empirical Bernstein Bounds for the Variance of Bounded Random Variables

Diego Martinez-Taboada, Aaditya Ramdas

We develop novel empirical Bernstein inequalities for the variance of bounded random variables. Our inequalities hold under constant conditional variance and mean, without further…

math.ST2026

Empirical Bernstein in smooth Banach spaces

Diego Martinez-Taboada, Aaditya Ramdas

Existing concentration bounds for bounded vector-valued random variables include extensions of the scalar Hoeffding and Bernstein inequalities. While the latter is typically tighte…

math.ST2026

Intrinsic-dimension empirical Bernstein inequalities for bounded self-adjoint operators

Diego Martinez-Taboada, Aaditya Ramdas

Operator-valued concentration inequalities are foundational to the analysis of modern high-dimensional statistics and randomized algorithms. However, standard oracle bounds are fre…

math.ST2026

Intrinsic dimension concentration inequalities for self-adjoint operators

Diego Martinez-Taboada, Aaditya Ramdas

We derive novel concentration inequalities for the operator norm of the sum of self-adjoint operators that do not explicitly depend on the underlying dimension of the operator, but…

math.ST2025

Mean Estimation in Banach Spaces Under Infinite Variance and Martingale Dependence

Justin Whitehouse, Ben Chugg, Diego Martinez-Taboada +1

We consider estimating the shared mean of a sequence of heavy-tailed random variables taking values in a Banach space. In particular, we revisit and extend a simple truncation-base…