Entropic herding

نویسندگان

چکیده

Abstract Herding is a deterministic algorithm used to generate data points regarded as random samples satisfying input moment conditions. This based on high-dimensional dynamical system and rooted in the maximum entropy principle of statistical inference. We propose an extension, entropic herding, which generates sequence distributions instead points. derived herding from optimization problem obtained using principle. Using proposed framework, we discussed closer connection between Specifically, interpreted original tractable version ideal output distribution mathematically represented. further how complex behavior contributes optimization. argued that extends probabilistic modeling. In contrast can smooth such both efficient probability density calculation sample generation become possible. To demonstrate viability these arguments this study, numerical experiments were conducted, including comparison with other conventional methods, synthetic real data.

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ژورنال

عنوان ژورنال: Statistics and Computing

سال: 2023

ISSN: ['0960-3174', '1573-1375']

DOI: https://doi.org/10.1007/s11222-022-10199-8