Derives vector-valued self-normalized concentration bounds for light-tailed processes beyond sub-Gaussianity, with applications to online linear regression and linear bandits.
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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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Vector-valued self-normalized concentration inequalities beyond sub-Gaussianity
Derives vector-valued self-normalized concentration bounds for light-tailed processes beyond sub-Gaussianity, with applications to online linear regression and linear bandits.
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Bernstein-type dimension-free concentration for self-normalised martingales
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.