Marco Mussi

According to our database, Marco Mussi authored at least 20 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Generalized Kernelized Bandits: Self-Normalized Bernstein-Like Dimension-Free Inequality and Regret Bounds.

Alberto Maria Metelli, Simone Drago, Marco Mussi

CoRR, August, 2025

Gym4ReaL: A Suite for Benchmarking Real-World Reinforcement Learning.

Davide Salaorni, Vincenzo De Paola, Samuele Delpero, Giovanni Dispoto, Paolo Bonetti, Alessio Russo, Giuseppe Calcagno, Francesco Trovò, Matteo Papini, Alberto Maria Metelli, Marco Mussi, Marcello Restelli

CoRR, July, 2025

Reusing Trajectories in Policy Gradients Enables Fast Convergence.

Alessandro Montenegro, Federico Mansutti, Marco Mussi, Matteo Papini, Alberto Maria Metelli

CoRR, June, 2025

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes.

Alessandro Montenegro, Leonardo Cesani, Marco Mussi, Matteo Papini, Alberto Maria Metelli

CoRR, June, 2025

A Refined Analysis of UCBVI.

Simone Drago, Marco Mussi, Alberto Maria Metelli

CoRR, February, 2025

Generalizing the Regret: an Analysis of Lower and Upper Bounds.

Marco Mussi, Alberto Maria Metelli

J. Artif. Intell. Res., 2025

Factored-reward bandits with intermediate observations: Regret minimization and best arm identification.

Marco Mussi, Simone Drago, Marcello Restelli, Alberto Maria Metelli

Artif. Intell., 2025

2024

Bridging Rested and Restless Bandits with Graph-Triggering: Rising and Rotting.

Gianmarco Genalti, Marco Mussi, Nicola Gatti, Marcello Restelli, Matteo Castiglioni, Alberto Maria Metelli

CoRR, 2024

State and Action Factorization in Power Grids.

Gianvito Losapio, Davide Beretta, Marco Mussi, Alberto Maria Metelli, Marcello Restelli

CoRR, 2024

Open Problem: Tight Bounds for Kernelized Multi-Armed Bandits with Bernoulli Rewards.

Marco Mussi, Simone Drago, Alberto Maria Metelli

CoRR, 2024

Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning.

Alessandro Montenegro, Marco Mussi, Matteo Papini, Alberto Maria Metelli

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Best Arm Identification for Stochastic Rising Bandits.

Marco Mussi, Alessandro Montenegro, Francesco Trovò, Marcello Restelli, Alberto Maria Metelli

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

Factored-Reward Bandits with Intermediate Observations.

Marco Mussi, Simone Drago, Marcello Restelli, Alberto Maria Metelli

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

Learning Optimal Deterministic Policies with Stochastic Policy Gradients.

Alessandro Montenegro, Marco Mussi, Alberto Maria Metelli, Matteo Papini

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

Graph-Triggered Rising Bandits.

Gianmarco Genalti, Marco Mussi, Nicola Gatti, Marcello Restelli, Matteo Castiglioni, Alberto Maria Metelli

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

Autoregressive Bandits.

Francesco Bacchiocchi, Gianmarco Genalti, Davide Maran, Marco Mussi, Marcello Restelli, Nicola Gatti, Alberto Maria Metelli

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

ARLO: A framework for Automated Reinforcement Learning.

Marco Mussi, Davide Lombarda, Alberto Maria Metelli, Francesco Trovò, Marcello Restelli

Expert Syst. Appl., August, 2023

Dynamical Linear Bandits.

Marco Mussi, Alberto Maria Metelli, Marcello Restelli

Proceedings of the International Conference on Machine Learning, 2023

Dynamic Pricing with Volume Discounts in Online Settings.

Marco Mussi, Gianmarco Genalti, Alessandro Nuara, Francesco Trovò, Marcello Restelli, Nicola Gatti

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Pricing the Long Tail by Explainable Product Aggregation and Monotonic Bandits.

Marco Mussi, Gianmarco Genalti, Francesco Trovò, Alessandro Nuara, Nicola Gatti, Marcello Restelli

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022