98 citations · 291 across the 38 of their papers we have counts for
10 papers · 1 filter
Distributed Bayesian Learning of Dynamic States
Mert Kayaalp, Virginia Bordignon, Stefan Vlaski +2
This work studies networked agents cooperating to track a dynamical state of nature under partial information. The proposed algorithm is a distributed Bayesian filtering algorithm…
Local Graph-homomorphic Processing for Privatized Distributed Systems
Elsa Rizk, Stefan Vlaski, Ali H. Sayed
We study the generation of dependent random numbers in a distributed fashion in order to enable privatized distributed learning by networked agents. We propose a method that we ref…
Networked Signal and Information Processing
Stefan Vlaski, Soummya Kar, Ali H. Sayed +1
The article reviews significant advances in networked signal and information processing, which have enabled in the last 25 years extending decision making and inference, optimizati…
Quantization for decentralized learning under subspace constraints
Roula Nassif, Stefan Vlaski, Marco Carpentiero +3
In this paper, we consider decentralized optimization problems where agents have individual cost functions to minimize subject to subspace constraints that require the minimizers a…
Robust and Efficient Aggregation for Distributed Learning
Stefan Vlaski, Christian Schroth, Michael Muma +1
Distributed learning paradigms, such as federated and decentralized learning, allow for the coordination of models across a collection of agents, and without the need to exchange r…
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…