Publications

2026

Learning to Coordinate via Quantum Entanglement in Multi-Agent Reinforcement Learning J. Gardiner, O. Romero, B. Tivnan, N. Dal Fabbro, G. J. Pappas under revision, arXiv 2602.08965, 2026.
Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning N. Dal Fabbro, M. Mesbahi, R. Mendes, J. Sousa, G. J. Pappas IEEE International Conference on Robotics and Automation (accepted), 2026.

Finite-Time Analysis of Over-the-Air Federated TD Learning N. Dal Fabbro, A. Mitra, R. W. Heath, L. Schenato, G. J. Pappas IEEE Transactions on Wireless Communications, 2025.
VREM-FL: Mobility-Aware Computation–Scheduling Co-Design for Vehicular Federated Learning L. Ballotta, N. Dal Fabbro, G. Perin, L. Schenato, M. Rossi, G. Piro IEEE Transactions on Vehicular Technology, 2025.
Conformal Risk Minimization with Variance Reduction S. Noorani, O. Romero, N. Dal Fabbro, H. Hassani, G. J. Pappas ICML 2025 Workshop on Reliable and Responsible Foundation Models , 2025.

DASA: Delay-Adaptive Multi-Agent Stochastic Approximation N. Dal Fabbro, A. Adibi, H. Vincent Poor, S. Kulkarni, A. Mitra, G. J. Pappas The 63rd IEEE Conference on Decision and Control, 2024
Finite-Time Analysis of Asynchronous Multi-Agent TD Learning N. Dal Fabbro, A. Adibi, A. Mitra, G. J. Pappas The American Control Conference (ACC), 2024.
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling A. Adibi, N. Dal Fabbro, L. Schenato, S. Kulkarni, H. V. Poor, G. J. Pappas, H. Hassani, A. Mitra The 27th International Conference on Artificial Intelligence and Statistics, 2024.
Anonymous Federated Learning via Named-Data Networking A. Agiollo, E. Bardhi, M. Conti, N. Dal Fabbro, R. Lazzeretti Future Generation Computer Systems, 2024.
Communication-Efficient Federated Reinforcement Learning: Recent Advances and Open Challenges N. Dal Fabbro, A. Mitra, G. J. Pappas Elsevier Encyclopedia of Systems and Control Engineering, 2024.
SHED: A Newton-type Algorithm for Federated Learning based on Incremental Hessian Eigenvector Sharing N. Dal Fabbro, S. Dey, M. Rossi, L. Schenato Automatica, 2024.

Federated TD Learning over Finite-Rate Erasure Channels: Linear Speedup under Markovian Sampling N. Dal Fabbro, A. Mitra, G. J. Pappas IEEE Control Systems Letters, 2023.
Q-SHED: Distributed Optimization at the Edge via Hessian Eigenvectors Quantization N. Dal Fabbro, M. Rossi, L. Schenato, S. Dey IEEE International Conference on Communications (Rome), 2023.
A CSI Dataset for Wireless Human Sensing on 80 MHz Wi-Fi Channels F. Meneghello, N. Dal Fabbro, D. Garlisi, I. Tinnirello, M. Rossi IEEE Communications Magazine, 2023.
Over-the-Air Federated TD Learning N. Dal Fabbro, A. Mitra, R. W. Heath, L. Schenato, G. J. Pappas MLSys Workshop on Resource-Constrained Learning in Wireless Networks, 2023.

Model-free Radio Map Estimation in Massive MIMO Systems via Semi-parametric Gaussian Regression N. Dal Fabbro, M. Rossi, G. Pillonetto, L. Schenato, G. Piro IEEE Wireless Communications Letters, 2022.
SHARP: Environment and Person-Independent Activity Recognition with Commodity IEEE 802.11 Access Points F. Meneghello, D. Garlisi, N. Dal Fabbro, I. Tinnirello, M. Rossi IEEE Transactions on Mobile Computing, 2022.