We consider distributed recursive estimation of consensus+innovations ty...
Recent works have shown that high probability metrics with stochastic
gr...
We propose a communication efficient approach for federated learning in
...
This paper studies probabilistic rates of convergence for
consensus+inno...
Deploying deep neural networks (DNNs) on IoT and mobile devices is a
cha...
We introduce a general framework for nonlinear stochastic gradient desce...
We propose a general approach for distance based clustering, using the
g...
We propose a parametric family of algorithms for personalized federated
...
The number of connected Internet of Things (IoT) devices within
cyber-ph...
The augmented Lagrangian method (ALM) is a classical optimization tool t...
We study detection of random signals corrupted by noise that over time s...