Publications related to Hellinger distance

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Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

Serge Vaudenay

The maximal achievable advantage of a (computationally unbounded) distinguisher to determine whether a source

Z

is distributed according to distribution

P_0

P_1

, when given access to one sample of

Z

, is characterized by the statistical distance ...

Springer, Cham2020

Hellinger distance

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Lower-bounds on the Bayesian Risk in Estimation Procedures via f–Divergences

Generalization Error Bounds Via Rényi-, f-Divergences and Maximal Leakage

Locally Differentially-Private Randomized Response for Discrete Distribution Learning

Robust Generalization via f−Mutual Information

Strong convergence of multivariate maxima

Double-Loop Unadjusted Langevin Algorithm

Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

Improving the arm-hand coordination in neuroprosthetics control with prior information from muscle activity

Unsupervised Learning of Representations for Lexical Entailment Detection

Study of constrained Brownian motion of nanoparticles near an interface using optical tweezers

Locally Differentially-Private Randomized Response for Discrete Distribution Learning

Improving the arm-hand coordination in neuroprosthetics control with prior information from muscle activity

Study of constrained Brownian motion of nanoparticles near an interface using optical tweezers

Unsupervised Learning of Representations for Lexical Entailment Detection

Strong convergence of multivariate maxima

Generalization Error Bounds Via Rényi-, f-Divergences and Maximal Leakage

Robust Generalization via f−Mutual Information

Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

Double-Loop Unadjusted Langevin Algorithm

Lower-bounds on the Bayesian Risk in Estimation Procedures via f–Divergences