3 citations · 5 across the 5 of their papers we have counts for
5 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…
Q-SHED: Distributed Optimization at the Edge via Hessian Eigenvectors Quantization
Nicolò Dal Fabbro, Michele Rossi, Luca Schenato +1
Edge networks call for communication efficient (low overhead) and robust distributed optimization (DO) algorithms. These are, in fact, desirable qualities for DO frameworks, such a…
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…