Giorgia Ramponi

CoRR, 2024

Improved Sample Complexity for Global Convergence of Actor-Critic Algorithms.

[BibT_eX]

[DOI]

CoRR, 2024

Preference Elicitation for Offline Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Stochastic Bilevel Optimization with Lower-Level Contextual Markov Decision Processes.

[BibT_eX]

[DOI]

CoRR, 2024

Truly No-Regret Learning in Constrained MDPs.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Provably Learning Nash Policies in Constrained Markov Potential Games.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023

Cancellation-Free Regret Bounds for Lagrangian Approaches in Constrained Markov Decision Processes.

[BibT_eX]

[DOI]

CoRR, 2023

On Imitation in Mean-field Games.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Do you pay for Privacy in Online learning?

[BibT_eX]

[DOI]

Amartya Sanyal

CoRR, 2022

Learning in Markov games: Can we exploit a general-sum opponent?

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Learning on streaming graphs with experience replay.

[BibT_eX]

[DOI]

Proceedings of the SAC '22: The 37th ACM/SIGAPP Symposium on Applied Computing, Virtual Event, April 25, 2022

Trust Region Policy Optimization with Optimal Transport Discrepancies: Duality and Algorithm for Continuous Actions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Active Exploration for Inverse Reinforcement Learning.

[BibT_eX]

[DOI]

David Lindner

Andreas Krause

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Newton-based Policy Search for Networked Multi-agent Reinforcement Learning.

[BibT_eX]

[DOI]

Giorgio Manganini

Simone Fioravanti

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021

Challenges and Opportunities in Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

PhD thesis, 2021

Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems.

[BibT_eX]

[DOI]

Amarildo Likmeta

Mach. Learn., 2021

Learning in Non-Cooperative Configurable Markov Decision Processes.

[BibT_eX]

[DOI]

Alessandro Concetti

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Provably Efficient Learning of Transferable Rewards.

[BibT_eX]

[DOI]

Alessandro Concetti

Proceedings of the 38th International Conference on Machine Learning, 2021

Newton Optimization on Helmholtz Decomposition for Continuous Games.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Content-based characterization of online social communities.

[BibT_eX]

[DOI]

Inf. Process. Manag., 2020

Newton-based Policy Optimization for Games.

[BibT_eX]

[DOI]

CoRR, 2020

Inverse Reinforcement Learning from a Gradient-based Learner.

[BibT_eX]

[DOI]

Gianluca Drappo

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Controlled Text Generation with Adversarial Learning.

[BibT_eX]

[DOI]

Federico Betti

Massimo Piccardi

Proceedings of the 13th International Conference on Natural Language Generation, 2020

Truly Batch Model-Free Inverse Reinforcement Learning about Multiple Intentions.

[BibT_eX]

[DOI]

Amarildo Likmeta

Andrea Tirinzoni