research
∙
05/18/2023
Q-SHED: Distributed Optimization at the Edge via Hessian Eigenvectors Quantization
Edge networks call for communication efficient (low overhead) and robust...
share
research
∙
05/13/2023
Network-GIANT: Fully distributed Newton-type optimization via harmonic Hessian consensus
This paper considers the problem of distributed multi-agent learning, wh...
research
∙
02/11/2022
A Newton-type algorithm for federated learning based on incremental Hessian eigenvector sharing
There is a growing interest in the decentralized optimization framework ...
research
∙
01/14/2020
Asymptotic Performance Analysis of Non-Bayesian Quickest Change Detection with an Energy Harvesting Sensor
In this paper, we consider a non-Bayesian sequential change detection ba...
research
∙
11/01/2019