Search Results for author:
Found 6 papers, 1 papers with code
VREM-FL: Mobility-Aware Computation-Scheduling Co-Design for Vehicular Federated Learning
In this domain, federated learning is one of the most effective and promising techniques for training global machine learning models, while preserving data privacy at the vehicles and optimizing communications resource usage.
To Compute or not to Compute? Adaptive Smart Sensing in Resource-Constrained Edge Computing
We consider a network of smart sensors for an edge computing application that sample a time-varying signal and send updates to a base station for remote global monitoring.
Can Competition Outperform Collaboration? The Role of Misbehaving Agents
We investigate a novel approach to resilient distributed optimization with quadratic costs in a multi-agent system prone to unexpected events that make some agents misbehave.
A Reinforcement Learning Approach to Sensing Design in Resource-Constrained Wireless Networked Control Systems
In this paper, we consider a wireless network of smart sensors (agents) that monitor a dynamical process and send measurements to a base station that performs global monitoring and decision-making.
Competition-Based Resilience in Distributed Quadratic Optimization
This paper proposes a novel approach to resilient distributed optimization with quadratic costs in a networked control system (e. g., wireless sensor network, power grid, robotic team) prone to external attacks (e. g., hacking, power outage) that cause agents to misbehave.
Optimal Network Topology of Multi-Agent Systems subject to Computation and Communication Latency (with proofs)
We study minimum-variance feedback-control design for a networked control system with retarded dynamics, where inter-agent communication is subject to latency.
