On Random Subset Generalization Error Bounds and the Stochastic Gradient Langevin Dynamics Algorithm. - Borja Rodríguez Gálvez; Germán Bassi; Ragnar Thobaben; Mikael Skoglund (ITW, 2020)

Upper Bounds on the Generalization Error of Private Algorithms. - Borja Rodríguez Gálvez; Germán Bassi; Mikael Skoglund (CoRR, 2020)

The Convex Information Bottleneck Lagrangian. - Borja Rodríguez Gálvez; Ragnar Thobaben; Mikael Skoglund (Entropy, 2020)

A Variational Approach to Privacy and Fairness. - Borja Rodríguez Gálvez; Ragnar Thobaben; Mikael Skoglund (ITW, 2021)

Tighter Expected Generalization Error Bounds via Wasserstein Distance. - Borja Rodríguez Gálvez; Germán Bassi; Ragnar Thobaben; Mikael Skoglund (NeurIPS, 2021)

Enforcing fairness in private federated learning via the modified method of differential multipliers. - Borja Rodríguez Gálvez; Filip Granqvist; Rogier C. van Dalen; Matt Seigel (CoRR, 2021)

Upper Bounds on the Generalization Error of Private Algorithms for Discrete Data. - Borja Rodríguez Gálvez; Germán Bassi; Mikael Skoglund (IEEE Trans. Inf. Theory, 2021)

An Information-Theoretic Analysis of Bayesian Reinforcement Learning. - Amaury Gouverneur; Borja Rodríguez Gálvez; Tobias J. Oechtering; Mikael Skoglund (Allerton, 2022)

Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization. - Mahdi Haghifam; Borja Rodríguez Gálvez; Ragnar Thobaben; Mikael Skoglund; Daniel M. Roy 001; Gintare Karolina Dziugaite (ALT, 2023)

The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning. - Borja Rodríguez Gálvez; Arno Blaas; Pau Rodríguez; Adam Golinski; Xavier Suau; Jason Ramapuram; Dan Busbridge; Luca Zappella (ICML, 2023)

Thompson Sampling Regret Bounds for Contextual Bandits with sub-Gaussian rewards. - Amaury Gouverneur; Borja Rodríguez Gálvez; Tobias J. Oechtering; Mikael Skoglund (ISIT, 2023)

A Note on Generalization Bounds for Losses with Finite Moments. - Borja Rodríguez Gálvez; Omar Rivasplata; Ragnar Thobaben; Mikael Skoglund (ISIT, 2024)

On Information Theoretic Fairness: Compressed Representations with Perfect Demographic Parity. - Amirreza Zamani; Borja Rodríguez Gálvez; Mikael Skoglund (ITW, 2024)

Chained Information-Theoretic bounds and Tight Regret Rate for Linear Bandit Problems. - Amaury Gouverneur; Borja Rodríguez Gálvez; Tobias J. Oechtering; Mikael Skoglund (CoRR, 2024)

A Coding-Theoretic Analysis of Hyperspherical Prototypical Learning Geometry. - Martin Lindström; Borja Rodríguez Gálvez; Ragnar Thobaben; Mikael Skoglund (CoRR, 2024)

An Information-Theoretic Approach to Generalization Theory. - Borja Rodríguez Gálvez; Ragnar Thobaben; Mikael Skoglund (CoRR, 2024)

An Information-Theoretic Analysis of Thompson Sampling for Logistic Bandits. - Amaury Gouverneur; Borja Rodríguez Gálvez; Tobias J. Oechtering; Mikael Skoglund (CoRR, 2024)

More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime validity. - Borja Rodríguez Gálvez; Ragnar Thobaben; Mikael Skoglund (J. Mach. Learn. Res., 2024)

An Information-Theoretic Approach to Generalization Theory. - Borja Rodríguez Gálvez (2024)

Information-Theoretic Minimax Regret Bounds for Reinforcement Learning based on Duality. - Raghav Bongole; Amaury Gouverneur; Borja Rodríguez Gálvez; Tobias J. Oechtering; Mikael Skoglund (ICASSP, 2025)

An Information-Theoretic Analysis of Thompson Sampling with Infinite Action Spaces. - Amaury Gouverneur; Borja Rodríguez Gálvez; Tobias J. Oechtering; Mikael Skoglund (ICASSP, 2025)

A Matrix Variational Auto-Encoder for Variant Effect Prediction in Pharmacogenes. - Antoine Honoré; Borja Rodríguez Gálvez; Yoomi Park; Yitian Zhou; Volker M. Lauschke; Ming Xiao (CoRR, 2025)