Search Results for author:
Found 7 papers, 1 papers with code
DASA: Delay-Adaptive Multi-Agent Stochastic Approximation
We consider a setting in which $N$ agents aim to speedup a common Stochastic Approximation (SA) problem by acting in parallel and communicating with a central server.
VREM-FL: Mobility-Aware Computation-Scheduling Co-Design for Vehicular Federated Learning
Assisted and autonomous driving are rapidly gaining momentum and will soon become a reality.
Q-SHED: Distributed Optimization at the Edge via Hessian Eigenvectors Quantization
Edge networks call for communication efficient (low overhead) and robust distributed optimization (DO) algorithms.
Federated TD Learning over Finite-Rate Erasure Channels: Linear Speedup under Markovian Sampling
Federated learning (FL) has recently gained much attention due to its effectiveness in speeding up supervised learning tasks under communication and privacy constraints.
A CSI Dataset for Wireless Human Sensing on 80 MHz Wi-Fi Channels
In the last years, several machine learning-based techniques have been proposed to monitor human movements from Wi-Fi channel readings.
SHED: A Newton-type algorithm for federated learning based on incremental Hessian eigenvector sharing
There is a growing interest in the distributed optimization framework that goes under the name of Federated Learning (FL).
SHARP: Environment and Person Independent Activity Recognition with Commodity IEEE 802.11 Access Points
SHARP is trained on data collected as a person performs seven different activities in a single environment.
