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20242026
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5 papers · 1 filter

stat.ML2026

Decentralized Machine Learning with Centralized Performance Guarantees via Gibbs Algorithms

Yaiza Bermudez, Samir M. Perlaza, Iñaki Esnaola

In this paper, it is shown, for the first time, that centralized performance is achievable in decentralized learning without sharing the local datasets. Specifically, when clients…

stat.ML2026

Empirical Risk Minimization with -Divergence Regularization

Francisco Daunas, Iñaki Esnaola, Samir M. Perlaza +1

In this paper, the solution to the empirical risk minimization problem with -divergence regularization (ERM-DR) is presented and conditions under which the solution also serv…

stat.ML2025

A Dual Optimization View to Empirical Risk Minimization with f-Divergence Regularization

Francisco Daunas, Iñaki Esnaola, Samir M. Perlaza

The dual formulation of empirical risk minimization with f-divergence regularization (ERM-fDR) is introduced. The solution of the dual optimization problem to the ERM-fDR is connec…

stat.ML2025

Generalization Error of -Divergence Stabilized Algorithms via Duality

Francisco Daunas, Iñaki Esnaola, Samir M. Perlaza +1

The solution to empirical risk minimization with -divergence regularization (ERM-DR) is extended to constrained optimization problems, establishing conditions for equivalence…

stat.ML2024

Equivalence of the Empirical Risk Minimization to Regularization on the Family of f-Divergences

Francisco Daunas, Iñaki Esnaola, Samir M. Perlaza +1

The solution to empirical risk minimization with -divergence regularization (ERM-DR) is presented under mild conditions on . Under such conditions, the optimal measure is…