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math.PR2026

Almost sure null bankruptcy of testing-by-betting strategies

Hongjian Wang, Shubhada Agrawal, Aaditya Ramdas

The bounded mean betting procedure serves as a crucial interface between the domains of (1) sequential, anytime-valid statistical inference, and (2) online learning and portfolio s…

math.PR2026

A variational approach to dimension-free self-normalized concentration

Ben Chugg, Aaditya Ramdas

We study the self-normalized concentration of vector-valued stochastic processes. We focus on bounds for "sub-" processes, a well-known and quite general class of process that…

math.PR2025

Time-uniform Chernoff bounds via nonnegative supermartingales

Steven R. Howard, Aaditya Ramdas, Jon McAuliffe +1

We develop a class of exponential bounds for the probability that a martingale sequence crosses a time-dependent linear threshold. Our key insight is that it is both natural and fr…

math.PR2025

Positive Semidefinite Matrix Supermartingales

Hongjian Wang, Aaditya Ramdas

We explore the asymptotic convergence and nonasymptotic maximal inequalities of supermartingales and backward submartingales in the space of positive semidefinite matrices. These a…

math.PR2025

Nonasymptotic and distribution-uniform Komlós-Major-Tusnády approximation

Ian Waudby-Smith, Martin Larsson, Aaditya Ramdas

We present nonasymptotic concentration inequalities for sums of independent and identically distributed random variables that yield asymptotic strong Gaussian approximations of Kom…

math.PR2025

Sharp Matrix Empirical Bernstein Inequalities

Hongjian Wang, Aaditya Ramdas

We present two sharp, closed-form empirical Bernstein inequalities for symmetric random matrices with bounded eigenvalues. By sharp, we mean that both inequalities adapt to the unk…