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Marco Mussi
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2020 – today
- 2025
[j3]Marco Mussi, Simone Drago
, Marcello Restelli
, Alberto Maria Metelli
:
Factored-reward bandits with intermediate observations: Regret minimization and best arm identification. Artif. Intell. 347: 104362 (2025)
[j2]Marco Mussi, Alberto Maria Metelli:
Generalizing the Regret: an Analysis of Lower and Upper Bounds. J. Artif. Intell. Res. 82: 1773-1806 (2025)
[c13]Simone Drago, Marco Mussi, Alberto Maria Metelli:
Towards Theoretical Understanding of Sequential Decision Making with Preference Feedback. ICML 2025
[c12]Simone Drago, Marco Mussi, Alberto Maria Metelli:
Sleeping Reinforcement Learning. ICML 2025
[c11]Simone Drago, Marco Mussi, Alberto Maria Metelli:
Position: Constants are Critical in Regret Bounds for Reinforcement Learning. ICML (Position Papers) 2025
[c10]Alessandro Montenegro, Marco Mussi, Matteo Papini, Alberto Maria Metelli:
Convergence Analysis of Policy Gradient Methods with Dynamic Stochasticity. ICML 2025
[i17]Simone Drago
, Marco Mussi, Alberto Maria Metelli:
A Refined Analysis of UCBVI. CoRR abs/2502.17370 (2025)
[i16]Alessandro Montenegro, Leonardo Cesani, Marco Mussi, Matteo Papini, Alberto Maria Metelli:
Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes. CoRR abs/2506.05953 (2025)
[i15]Alessandro Montenegro, Federico Mansutti, Marco Mussi, Matteo Papini, Alberto Maria Metelli:
Reusing Trajectories in Policy Gradients Enables Fast Convergence. CoRR abs/2506.06178 (2025)
[i14]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:
Gym4ReaL: A Suite for Benchmarking Real-World Reinforcement Learning. CoRR abs/2507.00257 (2025)
[i13]Alberto Maria Metelli, Simone Drago, Marco Mussi:
Generalized Kernelized Bandits: Self-Normalized Bernstein-Like Dimension-Free Inequality and Regret Bounds. CoRR abs/2508.01681 (2025)
[i12]Carlo Fabrizio, Gianvito Losapio, Marco Mussi, Alberto Maria Metelli, Marcello Restelli:
Power Grid Control with Graph-Based Distributed Reinforcement Learning. CoRR abs/2509.02861 (2025)
[i11]Marco Mussi, Marcello Restelli:
Online Dynamic Pricing of Complementary Products. CoRR abs/2511.22291 (2025)- 2024
[c9]Francesco Bacchiocchi, Gianmarco Genalti, Davide Maran, Marco Mussi, Marcello Restelli, Nicola Gatti, Alberto Maria Metelli:
Autoregressive Bandits. AISTATS 2024: 937-945
[c8]Gianmarco Genalti, Marco Mussi, Nicola Gatti, Marcello Restelli, Matteo Castiglioni, Alberto Maria Metelli:
Graph-Triggered Rising Bandits. ICML 2024
[c7]Alessandro Montenegro, Marco Mussi, Alberto Maria Metelli, Matteo Papini:
Learning Optimal Deterministic Policies with Stochastic Policy Gradients. ICML 2024
[c6]Marco Mussi, Simone Drago, Marcello Restelli, Alberto Maria Metelli:
Factored-Reward Bandits with Intermediate Observations. ICML 2024
[c5]Marco Mussi, Alessandro Montenegro, Francesco Trovò, Marcello Restelli, Alberto Maria Metelli:
Best Arm Identification for Stochastic Rising Bandits. ICML 2024
[c4]Alessandro Montenegro, Marco Mussi, Matteo Papini, Alberto Maria Metelli:
Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning. NeurIPS 2024
[i10]Alessandro Montenegro, Marco Mussi, Alberto Maria Metelli, Matteo Papini:
Learning Optimal Deterministic Policies with Stochastic Policy Gradients. CoRR abs/2405.02235 (2024)
[i9]Marco Mussi, Simone Drago
, Alberto Maria Metelli:
Open Problem: Tight Bounds for Kernelized Multi-Armed Bandits with Bernoulli Rewards. CoRR abs/2407.06321 (2024)
[i8]Alessandro Montenegro, Marco Mussi, Matteo Papini, Alberto Maria Metelli:
Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning. CoRR abs/2407.10775 (2024)
[i7]Gianvito Losapio, Davide Beretta, Marco Mussi, Alberto Maria Metelli, Marcello Restelli:
State and Action Factorization in Power Grids. CoRR abs/2409.04467 (2024)
[i6]Gianmarco Genalti, Marco Mussi, Nicola Gatti, Marcello Restelli, Matteo Castiglioni, Alberto Maria Metelli:
Bridging Rested and Restless Bandits with Graph-Triggering: Rising and Rotting. CoRR abs/2409.05980 (2024)- 2023
[j1]Marco Mussi
, Davide Lombarda
, Alberto Maria Metelli
, Francesco Trovò
, Marcello Restelli
:
ARLO: A framework for Automated Reinforcement Learning. Expert Syst. Appl. 224: 119883 (2023)
[c3]Marco Mussi, Gianmarco Genalti, Alessandro Nuara, Francesco Trovò, Marcello Restelli, Nicola Gatti:
Dynamic Pricing with Volume Discounts in Online Settings. AAAI 2023: 15560-15568
[c2]Marco Mussi, Alberto Maria Metelli, Marcello Restelli:
Dynamical Linear Bandits. ICML 2023: 25563-25587
[i5]Marco Mussi, Alessandro Montenegro, Francesco Trovò, Marcello Restelli, Alberto Maria Metelli:
Best Arm Identification for Stochastic Rising Bandits. CoRR abs/2302.07510 (2023)- 2022
[c1]Marco Mussi
, Gianmarco Genalti, Francesco Trovò, Alessandro Nuara, Nicola Gatti, Marcello Restelli:
Pricing the Long Tail by Explainable Product Aggregation and Monotonic Bandits. KDD 2022: 3623-3633
[i4]Marco Mussi, Davide Lombarda, Alberto Maria Metelli, Francesco Trovò, Marcello Restelli:
ARLO: A Framework for Automated Reinforcement Learning. CoRR abs/2205.10416 (2022)
[i3]Marco Mussi, Alberto Maria Metelli, Marcello Restelli:
Dynamical Linear Bandits. CoRR abs/2211.08997 (2022)
[i2]Marco Mussi, Gianmarco Genalti, Alessandro Nuara, Francesco Trovò, Marcello Restelli, Nicola Gatti:
Dynamic Pricing with Volume Discounts in Online Settings. CoRR abs/2211.09612 (2022)
[i1]Francesco Bacchiocchi, Gianmarco Genalti, Davide Maran, Marco Mussi, Marcello Restelli, Nicola Gatti, Alberto Maria Metelli:
Autoregressive Bandits. CoRR abs/2212.06251 (2022)
Coauthor Index

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last updated on 2026-02-04 23:57 CET by the dblp team
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