Search Results for author: Borja Rodríguez-Gálvez

Found 6 papers, 1 papers with code

An Information-Theoretic Analysis of Bayesian Reinforcement Learning

no code implementations18 Jul 2022 Amaury Gouverneur, Borja Rodríguez-Gálvez, Tobias J. Oechtering, Mikael Skoglund

Building on the framework introduced by Xu and Raginksy [1] for supervised learning problems, we study the best achievable performance for model-based Bayesian reinforcement learning problems.


Enforcing fairness in private federated learning via the modified method of differential multipliers

no code implementations17 Sep 2021 Borja Rodríguez-Gálvez, Filip Granqvist, Rogier Van Dalen, Matt Seigel

This paper introduces an algorithm to enforce group fairness in private federated learning, where users' data does not leave their devices.

BIG-bench Machine Learning Fairness +1

On Random Subset Generalization Error Bounds and the Stochastic Gradient Langevin Dynamics Algorithm

no code implementations21 Oct 2020 Borja Rodríguez-Gálvez, Germán Bassi, Ragnar Thobaben, Mikael Skoglund

In this work, we unify several expected generalization error bounds based on random subsets using the framework developed by Hellstr\"om and Durisi [1].

A Variational Approach to Privacy and Fairness

2 code implementations11 Jun 2020 Borja Rodríguez-Gálvez, Ragnar Thobaben, Mikael Skoglund

In this article, we propose a new variational approach to learn private and/or fair representations.

Fairness Representation Learning

Upper Bounds on the Generalization Error of Private Algorithms for Discrete Data

no code implementations12 May 2020 Borja Rodríguez-Gálvez, Germán Bassi, Mikael Skoglund

In this work, we study the generalization capability of algorithms from an information-theoretic perspective.

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