Inspired by a recent study by Christensen and Popovski on secure 2-user
...
The Σ-QMAC problem is introduced, involving S servers, K classical
(𝔽_d)...
Linear computations over quantum many-to-one communication networks offe...
Federated Learning (FL) enables machine learning model training on
distr...
Much of the value that IoT (Internet-of-Things) devices bring to “smart”...
Linear computation broadcast (LCBC) refers to a setting with d dimension...
The K User Linear Computation Broadcast (LCBC) problem is comprised of d...
This paper studies faithful explanations for Graph Neural Networks (GNNs...
Distributed methods for training models on graph datasets have recently ...
Graph Convolutional Networks (GCNs) are a popular method from graph
repr...
We study the problem of clustering nodes in a dynamic graph, where the
c...