| 2025 | ICASSP | Information-Theoretic Minimax Regret Bounds for Reinforcement Learning based on Duality. | Raghav Bongole, Amaury Gouverneur, Borja Rodrguez Glvez, Tobias J. Oechtering, Mikael Skoglund |
| 2025 | ICASSP | An Information-Theoretic Analysis of Thompson Sampling with Infinite Action Spaces. | Amaury Gouverneur, Borja Rodrguez Glvez, Tobias J. Oechtering, Mikael Skoglund |
| 2024 | ISIT | A Note on Generalization Bounds for Losses with Finite Moments. | Borja Rodrguez Glvez, Omar Rivasplata, Ragnar Thobaben, Mikael Skoglund |
| 2024 | ITW | On Information Theoretic Fairness: Compressed Representations with Perfect Demographic Parity. | Amirreza Zamani, Borja Rodrguez Glvez, Mikael Skoglund |
| 2023 | ALT | Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization. | Mahdi Haghifam, Borja Rodrguez Glvez, Ragnar Thobaben, Mikael Skoglund, Daniel M. Roy, Gintare Karolina Dziugaite |
| 2023 | ICML | The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning. | Borja Rodrguez Glvez, Arno Blaas, Pau Rodrguez, Adam Golinski, Xavier Suau, Jason Ramapuram, Dan Busbridge, Luca Zappella |
| 2023 | ISIT | Thompson Sampling Regret Bounds for Contextual Bandits with sub-Gaussian rewards. | Amaury Gouverneur, Borja Rodrguez Glvez, Tobias J. Oechtering, Mikael Skoglund |
| 2021 | ITW | A Variational Approach to Privacy and Fairness. | Borja Rodrguez Glvez, Ragnar Thobaben, Mikael Skoglund |
| 2020 | ITW | On Random Subset Generalization Error Bounds and the Stochastic Gradient Langevin Dynamics Algorithm. | Borja Rodrguez Glvez, Germn Bassi, Ragnar Thobaben, Mikael Skoglund |