Borja Rodríguez Gálvez

35 papers A* 2B 6Misc 2Journal 23Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
A Matrix Variational Auto-Encoder for Variant Effect Prediction in Pharmacogenes.
CoRR
Antoine Honoré, Borja Rodríguez Gálvez, Yoomi Park, Yitian Zhou, Volker M. Lauschke, Ming Xiao
2025 Misc conf
An Information-Theoretic Analysis of Thompson Sampling with Infinite Action Spaces.
ICASSP
Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias J. Oechtering, Mikael Skoglund
2025 J jnl
An Information-Theoretic Analysis of Thompson Sampling with Infinite Action Spaces.
CoRR
Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias J. Oechtering, Mikael Skoglund
2025 Misc conf
Information-Theoretic Minimax Regret Bounds for Reinforcement Learning based on Duality.
ICASSP
Raghav Bongole, Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias J. Oechtering, Mikael Skoglund
2024 J jnl
A Coding-Theoretic Analysis of Hyperspherical Prototypical Learning Geometry.
CoRR
Martin Lindström, Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund
2024 B conf
A Note on Generalization Bounds for Losses with Finite Moments.
ISIT
Borja Rodríguez Gálvez, Omar Rivasplata, Ragnar Thobaben, Mikael Skoglund
2024 J jnl
A note on generalization bounds for losses with finite moments.
CoRR
Borja Rodríguez Gálvez, Omar Rivasplata, Ragnar Thobaben, Mikael Skoglund
2024 J jnl
An Information-Theoretic Analysis of Thompson Sampling for Logistic Bandits.
CoRR
Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias J. Oechtering, Mikael Skoglund
2024 J jnl
An Information-Theoretic Approach to Generalization Theory.
CoRR
Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund
2024 — —
An Information-Theoretic Approach to Generalization Theory.
Borja Rodríguez Gálvez
2024 J jnl
Chained Information-Theoretic bounds and Tight Regret Rate for Linear Bandit Problems.
CoRR
Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias J. Oechtering, Mikael Skoglund
2024 J jnl
Information-Theoretic Minimax Regret Bounds for Reinforcement Learning based on Duality.
CoRR
Raghav Bongole, Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias J. Oechtering, Mikael Skoglund
2024 J jnl
More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime validity.
J. Mach. Learn. Res.
Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund
2024 J jnl
On Information Theoretic Fairness: Compressed Representations With Perfect Demographic Parity.
CoRR
Amirreza Zamani, Borja Rodríguez Gálvez, Mikael Skoglund
2024 B conf
On Information Theoretic Fairness: Compressed Representations with Perfect Demographic Parity.
ITW
Amirreza Zamani, Borja Rodríguez Gálvez, Mikael Skoglund
2023 B conf
Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization.
ALT
Mahdi Haghifam, Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund, Daniel M. Roy, Gintare Karolina Dziugaite
2023 J jnl
More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime-validity.
CoRR
Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund
2023 A* conf
The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning.
ICML
Borja Rodríguez Gálvez, Arno Blaas, Pau Rodríguez, Adam Golinski, Xavier Suau, Jason Ramapuram, Dan Busbridge, Luca Zappella
2023 J jnl
The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning.
CoRR
Borja Rodríguez Gálvez, Arno Blaas, Pau Rodríguez, Adam Golinski, Xavier Suau, Jason Ramapuram, Dan Busbridge, Luca Zappella
2023 B conf
Thompson Sampling Regret Bounds for Contextual Bandits with sub-Gaussian rewards.
ISIT
Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias J. Oechtering, Mikael Skoglund
2023 J jnl
Thompson Sampling Regret Bounds for Contextual Bandits with sub-Gaussian rewards.
CoRR
Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias J. Oechtering, Mikael Skoglund
2022 — conf
An Information-Theoretic Analysis of Bayesian Reinforcement Learning.
Allerton
Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias J. Oechtering, Mikael Skoglund
2022 J jnl
An Information-Theoretic Analysis of Bayesian Reinforcement Learning.
CoRR
Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias J. Oechtering, Mikael Skoglund
2022 J jnl
Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization.
CoRR
Mahdi Haghifam, Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund, Daniel M. Roy, Gintare Karolina Dziugaite
2021 B conf
A Variational Approach to Privacy and Fairness.
ITW
Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund
2021 J jnl
Enforcing fairness in private federated learning via the modified method of differential multipliers.
CoRR
Borja Rodríguez Gálvez, Filip Granqvist, Rogier C. van Dalen, Matt Seigel
2021 A* conf
Tighter Expected Generalization Error Bounds via Wasserstein Distance.
NeurIPS
Borja Rodríguez Gálvez, Germán Bassi, Ragnar Thobaben, Mikael Skoglund
2021 J jnl
Tighter expected generalization error bounds via Wasserstein distance.
CoRR
Borja Rodríguez Gálvez, Germán Bassi, Ragnar Thobaben, Mikael Skoglund
2021 J jnl
Upper Bounds on the Generalization Error of Private Algorithms for Discrete Data.
IEEE Trans. Inf. Theory
Borja Rodríguez Gálvez, Germán Bassi, Mikael Skoglund
2020 J jnl
A Variational Approach to Privacy and Fairness.
CoRR
Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund
2020 B conf
On Random Subset Generalization Error Bounds and the Stochastic Gradient Langevin Dynamics Algorithm.
ITW
Borja Rodríguez Gálvez, Germán Bassi, Ragnar Thobaben, Mikael Skoglund
2020 J jnl
On Random Subset Generalization Error Bounds and the Stochastic Gradient Langevin Dynamics Algorithm.
CoRR
Borja Rodríguez Gálvez, Germán Bassi, Ragnar Thobaben, Mikael Skoglund
2020 J jnl
The Convex Information Bottleneck Lagrangian.
Entropy
Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund
2020 J jnl
Upper Bounds on the Generalization Error of Private Algorithms.
CoRR
Borja Rodríguez Gálvez, Germán Bassi, Mikael Skoglund
2019 J jnl
The Convex Information Bottleneck Lagrangian.
CoRR
Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund