Variational representation of weighted divergencies and error exponent function

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Weighted divergencies and the exponential error function can be formulated using variational representations, which have direct implications for statistical inference and entropic optimal transport. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

Mark Kelbert

doi:10.1080/02331888.2026.2727581

September 7, 2026Statistics

Variational representation of weighted divergencies and error exponent function

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Key Points

The objective is to establish variational formulations for weighted divergences and exponential error functions while examining their theoretical consequences for probability modeling.
Derived variational representations for weighted divergences across probability distributions.
Formulated dual variational characterizations for the exponential error and error exponent functions.
Evaluated analytical implications for statistical inference procedures and entropic optimal transport problems.
Established analytical variational representations for weighted divergences and exponential error functions.
Demonstrated direct theoretical connections between the derived variational bounds, inference estimators, and entropic optimal transport frameworks.

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Implication

Mathematical analysis derives variational representations for weighted divergences and error exponent functions, highlighting applications in statistical inference and entropic optimal transport.

Abstract

We present variational representations for the weighted divergencies and exponential error function, and discuss implications for the statistical inference and entropic optimal transport.

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Mark Kelbert (2026) studied this question.

synapsesocial.com/papers/6a9fd82f58e84d0ff5b477c4 https://doi.org/10.1080/02331888.2026.2727581

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Variational representation of weighted divergencies and error exponent function

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Variational representation of weighted divergencies and error exponent function

Key Points

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Implication

Abstract

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