Derives closed-form Rényi rate-distortion-perception functions for Gaussian sources showing a feasible variance interval under perception constraints and establishes a Rényi-generalized strong functional representation lemma with alpha-dependent phase transitions in coding complexity.
A unified framework for one-shot achievability via the poisson matching lemma,
3 Pith papers cite this work. Polarity classification is still indexing.
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cs.IT 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
Sharper information-theoretic generalization bounds for differentially private algorithms obtained via typicality arguments that improve prior mutual-information results and add new maximal-leakage bounds.
Disjoint codebooks create a codebook diversity gain in one-shot broadcast JSCC distinct from channel diversity, with hybrid partitioning outperforming fully shared or fully disjoint codebooks.
citing papers explorer
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On the R\'enyi Rate-Distortion-Perception Function and Functional Representations
Derives closed-form Rényi rate-distortion-perception functions for Gaussian sources showing a feasible variance interval under perception constraints and establishes a Rényi-generalized strong functional representation lemma with alpha-dependent phase transitions in coding complexity.
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On the Generalization Error of Differentially Private Algorithms via Typicality
Sharper information-theoretic generalization bounds for differentially private algorithms obtained via typicality arguments that improve prior mutual-information results and add new maximal-leakage bounds.
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One-Shot Broadcast Joint Source-Channel Coding with Codebook Diversity
Disjoint codebooks create a codebook diversity gain in one-shot broadcast JSCC distinct from channel diversity, with hybrid partitioning outperforming fully shared or fully disjoint codebooks.