L. Ballotta, N. Dal Fabbro, G. Perin, L. Schenato, M. Rossi, G. Piro, "VREM-FL: Mobility-Aware Computation-Scheduling Co-Design for Vehicular Federated Learning", in IEEE Transactions on Vehicular Technology, 2024
DASA: Delay-Adaptive Multi-Agent Stochastic ApproximationN. Dal Fabbro, A. Adibi, H. Vincent Poor, Sanjeev Kulkarni, Aritra Mitra, George J. Pappas, "DASA: Delay-Adaptive Multi-Agent Stochastic Approximation", accepted at the 63rd IEEE Conference on Decision and Control, preprint available arXiv:2403.17247, 2024
Finite-Time Analysis of Asynchronous Multi-Agent TD LearningN. Dal Fabbro, A. Adibi, Aritra Mitra, George J. Pappas, "Finite-Time Analysis of Asynchronous Multi-Agent TD Learning", Proceedings of the American Control Conference, 2024
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian SamplingA. Adibi, N. Dal Fabbro, Luca Schenato, Sanjeev Kulkarni, H. Vincent Poor, George J. Pappas, Hamed Hassani and Aritra Mitra, "Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling", The 27th International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Anonymous Federated Learning via Named-Data NetworkingA. Agiollo, E. Bardhi, M. Conti, N. Dal Fabbro, R. Lazzeretti, "Anonymous Federated Learning via Named-Data Networking", Future Generation Computer Systems, 2024
Conformal Risk Minimization with Variance ReductionS. Noorani, O. Romero, N. Dal Fabbro, H. Hassani, and G. J. Pappas. "Conformal Risk Minimization with Variance Reduction", under revision, preprint available: arXiv preprint arXiv:2411.01696, 2024
Communication-Efficient Federated Reinforcement Learning: Recent Advances and Open ChallengesN. Dal Fabbro, A. Mitra, G. J. Pappas, "Communication-Efficient Federated Reinforcement Learning: Recent Advances and Open Challenges", Elsevier Encyclopedia of Systems and Control Engineering, 2024, 2024
N. Dal Fabbro, A. Mitra, G. J. Pappas, "Federated TD Learning over Finite-Rate Erasure Channels: Linear Speedup under Markovian Sampling", IEEE Control Systems Letters, 2023
Q-SHED: Distributed Optimization at the Edge via Hessian Eigenvectors QuantizationN. Dal Fabbro, M. Rossi, L. Schenato, S. Dey, "Q-SHED: Distributed Optimization at the Edge via Hessian Eigenvectors Quantization", IEEE International Conference on Communications (ICC), Rome, Italy, 2023
A CSI Dataset for Wireless Human Sensing on 80 MHz Wi-Fi ChannelsF. Meneghello, N. Dal Fabbro, D. Garlisi, I. Tinnirello and M. Rossi, "A CSI Dataset for Wireless Human Sensing on 80 MHz Wi-Fi Channels", IEEE Communications Magazine, 2023
Over-the-Air Federated TD LearningN. Dal Fabbro, A. Mitra, R. W. Heath, L. Schenato, G. J. Pappas, "Over-the-Air Federated TD Learning", MLSys 2023 Workshop on Resource-Constrained Learning in Wireless Networks, Miami, Florida, 2023
SHED: A Newton-type algorithm for federated learning based on incremental Hessian eigenvector sharingN. Dal Fabbro, S. Dey, M. Rossi, L. Schenato (2023). "SHED: A Newton-type algorithm for federated learning based on incremental Hessian eigenvector sharing", Automatica, 2023
N. Dal Fabbro, M. Rossi, G. Pillonetto, L. Schenato and G. Piro, "Model-free radio map estimation in massive MIMO systems via semi-parametric Gaussian regression," in IEEE Wireless Communications Letters, 2022
SHARP: Environment and Person Independent Activity Recognition with Commodity IEEE 802.11 Access PointsF. Meneghello, D. Garlisi, N. Dal Fabbro, I. Tinnirello and M. Rossi, "SHARP: Environment and Person Independent Activity Recognition with Commodity IEEE 802.11 Access Points," in IEEE Transactions on Mobile Computing, 2022