4 citations · 5 across the 11 of their papers we have counts for
4 papers · 1 filter
Doubly Adaptive Social Learning
Marco Carpentiero, Virginia Bordignon, Vincenzo Matta +1
In social learning, a network of agents assigns probability scores (beliefs) to some hypotheses of interest, which rule the generation of local streaming data observed by each agen…
Non-Asymptotic Performance of Social Machine Learning Under Limited Data
Ping Hu, Virginia Bordignon, Mert Kayaalp +1
This paper studies the probability of error associated with the social machine learning framework, which involves an independent training phase followed by a cooperative decision-m…
Dencentralized learning in the presence of low-rank noise
Roula Nassif, Virginia Bordignon, Stefan Vlaski +1
Observations collected by agents in a network may be unreliable due to observation noise or interference. This paper proposes a distributed algorithm that allows each node to impro…
Learning from Heterogeneous Data Based on Social Interactions over Graphs
Virginia Bordignon, Stefan Vlaski, Vincenzo Matta +1
This work proposes a decentralized architecture, where individual agents aim at solving a classification problem while observing streaming features of different dimensions and aris…