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20232026
most citedAnalyzing α-divergence in Gaussian Rate-Distortion-Perception Theory

3 citations · 3 across the 9 of their papers we have counts for

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9 papers

cs.LG2026

DP-IVON-Gradsq: Differentially Private Squared-Gradient Improved Variational Online Newton

Nour Jamoussi, Ikram Dridi, Giuseppe Serra +1

Differential privacy provides formal privacy guarantees for training neural networks on sensitive data, while Bayesian deep learning offers a principled framework for uncertainty-a…

cs.IT2026

Rate-Distortion-Perception Theory: Redefining the Fundamental Limits of Information Representation

Photios A. Stavrou, Giuseppe Serra, Marios Kountouris

Classical rate-distortion (RD) theory has long established the fundamental limits of lossy compression by quantifying the minimum number of bits required to represent a source unde…

cs.IT2025★ 3 cited

Analyzing α-divergence in Gaussian Rate-Distortion-Perception Theory

Martha V. Sourla, Giuseppe Serra, Photios A. Stavrou +1

The problem of estimating the information rate distortion perception function (RDPF), which is a relevant information-theoretic quantity in goal-oriented lossy compression and sema…

cs.LG2025

Cost-Free Personalization via Information-Geometric Projection in Bayesian Federated Learning

Nour Jamoussi, Giuseppe Serra, Photios A. Stavrou +1

Bayesian Federated Learning (BFL) combines uncertainty modeling with decentralized training, enabling the development of personalized and reliable models under data heterogeneity a…

cs.IT2025

On the Rate-Distortion-Perception Function for Gaussian Processes

Giuseppe Serra, Photios A. Stavrou, Marios Kountouris

In this paper, we investigate the rate-distortion-perception function (RDPF) of a source modeled by a Gaussian Process (GP) on a measure space under mean squared error (MSE) di…

cs.LG2024

Information-Geometric Barycenters for Bayesian Federated Learning

Nour Jamoussi, Giuseppe Serra, Photios A. Stavrou +1

Federated learning (FL) is a widely used and impactful distributed optimization framework that achieves consensus through averaging locally trained models. While effective, this ap…

cs.IT2024

Alternating Minimization Schemes for Computing Rate-Distortion-Perception Functions with -Divergence Perception Constraints

Giuseppe Serra, Photios A. Stavrou, Marios Kountouris

We study the computation of the rate-distortion-perception function (RDPF) for discrete memoryless sources subject to a single-letter average distortion constraint and a perception…

cs.IT2024

Copula-based Estimation of Continuous Sources for a Class of Constrained Rate-Distortion-Functions

Giuseppe Serra, Photios A. Stavrou, Marios Kountouris

We present a new method to estimate the rate-distortion-perception function in the perfect realism regime (PR-RDPF), for multivariate continuous sources subject to a single-letter…

cs.IT2023

On the Computation of the Gaussian Rate-Distortion-Perception Function

Giuseppe Serra, Photios A. Stavrou, Marios Kountouris

In this paper, we study the computation of the rate-distortion-perception function (RDPF) for a multivariate Gaussian source under mean squared error (MSE) distortion and, respecti…