10 citations · 15 across the 6 of their papers we have counts for
6 papers
Conformal Risk Minimization with Variance Reduction
Sima Noorani, Orlando Romero, Nicolo Dal Fabbro +2
Conformal prediction (CP) is a distribution-free framework for achieving probabilistic guarantees on black-box models. CP is generally applied to a model post-training. Recent rese…
Finite-Time Analysis of Asynchronous Multi-Agent TD Learning
Nicolò Dal Fabbro, Arman Adibi, Aritra Mitra +1
Recent research endeavours have theoretically shown the beneficial effect of cooperation in multi-agent reinforcement learning (MARL). In a setting involving agents, this benef…
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling
Arman Adibi, Nicolo Dal Fabbro, Luca Schenato +5
Motivated by applications in large-scale and multi-agent reinforcement learning, we study the non-asymptotic performance of stochastic approximation (SA) schemes with delayed updat…
DASA: Delay-Adaptive Multi-Agent Stochastic Approximation
Nicolò Dal Fabbro, Arman Adibi, H. Vincent Poor +3
We consider a setting in which agents aim to speedup a common Stochastic Approximation (SA) problem by acting in parallel and communicating with a central server. We assume tha…
VREM-FL: Mobility-Aware Computation-Scheduling Co-Design for Vehicular Federated Learning
Luca Ballotta, Nicolò Dal Fabbro, Giovanni Perin +3
Assisted and autonomous driving are rapidly gaining momentum and will soon become a reality. Artificial intelligence and machine learning are regarded as key enablers thanks to the…
Federated TD Learning over Finite-Rate Erasure Channels: Linear Speedup under Markovian Sampling
Nicolò Dal Fabbro, Aritra Mitra, George J. Pappas
Federated learning (FL) has recently gained much attention due to its effectiveness in speeding up supervised learning tasks under communication and privacy constraints. However, w…