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Furthermore, for eachn ∈ N+, let ¯M0 = 1 and ¯Mn := ¯Mn(πn|B) and define Jn(x) = ⟨Sn, x⟩ − ⟨x, Hnx⟩/2

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Bernstein-type dimension-free concentration for self-normalised martingales

math.PR · 2025-07-28 · unverdicted · novelty 7.0

Introduces a dimension-free Bernstein-type concentration inequality for self-normalised martingales and applies it to ellipsoidal confidence sequences in logistic regression with Hilbert-valued covariates and instance-adaptive regret bounds for Hilbert-armed logistic bandits.

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  • Bernstein-type dimension-free concentration for self-normalised martingales math.PR · 2025-07-28 · unverdicted · none · ref 8

    Introduces a dimension-free Bernstein-type concentration inequality for self-normalised martingales and applies it to ellipsoidal confidence sequences in logistic regression with Hilbert-valued covariates and instance-adaptive regret bounds for Hilbert-armed logistic bandits.