It is shown that the zero placement that limits the privacy loss also raises the floor on the adversary's reconstruction error, and the log-likelihood ratio between the releases of two adjacent topologies is governed by the distances from each zero to the graph frequencies of the two GSOs.
Andrew Campbell, Chen-Yu Zhang, Hang Liu et al.· 0 citations
A unified information-theoretic framework for dimensionality reduction of finite distributions is provided, clarifying the structural role of f -divergence-based entropies and negentropies and their relation to classical information measures.
M. Sbert, Min Chen, Jordi Poch et al.· Journal of Advanced Computat...· 0 citations
It is proved that both recover the infinite-autoregressive representation of the true process at a near-parametric rate in fixed dimension, so the truncation introduces no asymptotic bias.
This paper proposes a novel flow matching method that overcomes the limitations of existing multi-marginal trajectory inference algorithms, using a GAN-inspired adversarial loss to fit neurally parametrised interpolant curves between source and target points such that the marginal distributions at intermediate time poi...
Oskar Kviman, Kirill Tamogashev, Nicola Branchini et al.· arXiv.org· 2 citations
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