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Borja Rodríguez Gálvez
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2020 – today
- 2024
- [b1]Borja Rodríguez Gálvez:
An Information-Theoretic Approach to Generalization Theory. Royal Institute of Technology, Stockholm, Sweden, 2024 - [j3]Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund:
More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime validity. J. Mach. Learn. Res. 25: 110:1-110:43 (2024) - [c9]Borja Rodríguez Gálvez, Omar Rivasplata, Ragnar Thobaben, Mikael Skoglund:
A Note on Generalization Bounds for Losses with Finite Moments. ISIT 2024: 2676-2681 - [c8]Amirreza Zamani, Borja Rodríguez Gálvez, Mikael Skoglund:
On Information Theoretic Fairness: Compressed Representations with Perfect Demographic Parity. ITW 2024: 25-30 - [i18]Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias J. Oechtering, Mikael Skoglund:
Chained Information-Theoretic bounds and Tight Regret Rate for Linear Bandit Problems. CoRR abs/2403.03361 (2024) - [i17]Borja Rodríguez Gálvez, Omar Rivasplata, Ragnar Thobaben, Mikael Skoglund:
A note on generalization bounds for losses with finite moments. CoRR abs/2403.16681 (2024) - [i16]Martin Lindström, Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund:
A Coding-Theoretic Analysis of Hyperspherical Prototypical Learning Geometry. CoRR abs/2407.07664 (2024) - [i15]Amirreza Zamani, Borja Rodríguez Gálvez, Mikael Skoglund:
On Information Theoretic Fairness: Compressed Representations With Perfect Demographic Parity. CoRR abs/2408.13168 (2024) - [i14]Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund:
An Information-Theoretic Approach to Generalization Theory. CoRR abs/2408.13275 (2024) - [i13]Raghav Bongole, Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias J. Oechtering, Mikael Skoglund:
Information-Theoretic Minimax Regret Bounds for Reinforcement Learning based on Duality. CoRR abs/2410.16013 (2024) - [i12]Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias J. Oechtering, Mikael Skoglund:
An Information-Theoretic Analysis of Thompson Sampling for Logistic Bandits. CoRR abs/2412.02861 (2024) - 2023
- [c7]Mahdi Haghifam, Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund, Daniel M. Roy, Gintare Karolina Dziugaite:
Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization. ALT 2023: 663-706 - [c6]Borja Rodríguez Gálvez, Arno Blaas, Pau Rodríguez, Adam Golinski, Xavier Suau, Jason Ramapuram, Dan Busbridge, Luca Zappella:
The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning. ICML 2023: 29143-29160 - [c5]Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias J. Oechtering, Mikael Skoglund:
Thompson Sampling Regret Bounds for Contextual Bandits with sub-Gaussian rewards. ISIT 2023: 1306-1311 - [i11]Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias J. Oechtering, Mikael Skoglund:
Thompson Sampling Regret Bounds for Contextual Bandits with sub-Gaussian rewards. CoRR abs/2304.13593 (2023) - [i10]Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund:
More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime-validity. CoRR abs/2306.12214 (2023) - [i9]Borja Rodríguez Gálvez, Arno Blaas, Pau Rodríguez, Adam Golinski, Xavier Suau, Jason Ramapuram, Dan Busbridge, Luca Zappella:
The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning. CoRR abs/2307.10907 (2023) - 2022
- [c4]Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias J. Oechtering, Mikael Skoglund:
An Information-Theoretic Analysis of Bayesian Reinforcement Learning. Allerton 2022: 1-7 - [i8]Amaury Gouverneur, Borja Rodríguez Gálvez, Tobias J. Oechtering, Mikael Skoglund:
An Information-Theoretic Analysis of Bayesian Reinforcement Learning. CoRR abs/2207.08735 (2022) - [i7]Mahdi Haghifam, Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund, Daniel M. Roy, Gintare Karolina Dziugaite:
Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization. CoRR abs/2212.13556 (2022) - 2021
- [j2]Borja Rodríguez Gálvez
, Germán Bassi
, Mikael Skoglund
:
Upper Bounds on the Generalization Error of Private Algorithms for Discrete Data. IEEE Trans. Inf. Theory 67(11): 7362-7379 (2021) - [c3]Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund:
A Variational Approach to Privacy and Fairness. ITW 2021: 1-6 - [c2]Borja Rodríguez Gálvez, Germán Bassi, Ragnar Thobaben, Mikael Skoglund:
Tighter Expected Generalization Error Bounds via Wasserstein Distance. NeurIPS 2021: 19109-19121 - [i6]Borja Rodríguez Gálvez, Germán Bassi, Ragnar Thobaben, Mikael Skoglund:
Tighter expected generalization error bounds via Wasserstein distance. CoRR abs/2101.09315 (2021) - [i5]Borja Rodríguez Gálvez, Filip Granqvist, Rogier C. van Dalen, Matt Seigel:
Enforcing fairness in private federated learning via the modified method of differential multipliers. CoRR abs/2109.08604 (2021) - 2020
- [j1]Borja Rodríguez Gálvez
, Ragnar Thobaben
, Mikael Skoglund
:
The Convex Information Bottleneck Lagrangian. Entropy 22(1): 98 (2020) - [c1]Borja Rodríguez Gálvez, Germán Bassi, Ragnar Thobaben, Mikael Skoglund:
On Random Subset Generalization Error Bounds and the Stochastic Gradient Langevin Dynamics Algorithm. ITW 2020: 1-5 - [i4]Borja Rodríguez Gálvez, Germán Bassi, Mikael Skoglund:
Upper Bounds on the Generalization Error of Private Algorithms. CoRR abs/2005.05889 (2020) - [i3]Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund:
A Variational Approach to Privacy and Fairness. CoRR abs/2006.06332 (2020) - [i2]Borja Rodríguez Gálvez, Germán Bassi, Ragnar Thobaben, Mikael Skoglund:
On Random Subset Generalization Error Bounds and the Stochastic Gradient Langevin Dynamics Algorithm. CoRR abs/2010.10994 (2020)
2010 – 2019
- 2019
- [i1]Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund:
The Convex Information Bottleneck Lagrangian. CoRR abs/1911.11000 (2019)
Coauthor Index

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