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F. Calmon

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Preprint Aug 2026

A Complete Characterization of Tensorizable $f$-divergences

Csiszar's formulation of the $f$-divergence introduced a vast family of functionals for quantifying dissimilarity between probability distributions. However, many applications in statistics and information theory rely only on a few $f$-divergences, such as the Kullback-Leibler divergence, the $\chi^2$-divergence, and t...

R. Cruz, F. Calmon, Qiang Yu · 1 citation · ⚡1
Preprint Sep 2026

Feedback Coding Enables Inference-Time Covert Agentic Communication

This work recast black-box black-box LLM steganography as a sequential communication problem with causal, noiseless feedback: every generated token is observed by both parties and can guide subsequent embedding.

Si-Dong Guo, Sajani Vithana, Atefeh Gilani et al. · 1 citation
Jul 2026

Optimal Domain-Aware Privacy Mechanisms for Synthetic Data Generation

This work considers normalized histograms as distribution estimators and characterize the asymptotically optimal domain-aware privacy mechanism within a specific class of DP mechanisms, and introduces PubMix, a public-data-aware DP mechanism that can be used in histogram-based data synthesis pipelines.

Sajani Vithana, Sangwon Jung, Haoyang Hu et al. · 0 citations

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