Quantization design for distributed optimization
We consider the problem of solving a distributed optimization problem using a distributed
computing platform, where the communication in the network is limited: each node can only …
computing platform, where the communication in the network is limited: each node can only …
Convergence of limited communication gradient methods
Distributed optimization increasingly plays a central role in economical and sustainable
operation of cyber-physical systems. Nevertheless, the complete potential of the technology …
operation of cyber-physical systems. Nevertheless, the complete potential of the technology …
Communication complexity of dual decomposition methods for distributed resource allocation optimization
Dual decomposition methods are among the most prominent approaches for finding
primal/dual saddle point solutions of resource allocation optimization problems. To deploy …
primal/dual saddle point solutions of resource allocation optimization problems. To deploy …
A consensus algorithm for networks with process noise and quantization error
In this paper we address the problem of quantized consensus where process noise or
external inputs corrupt the state of each agent at each iteration. We propose a quantized …
external inputs corrupt the state of each agent at each iteration. We propose a quantized …
Design of a distributed quantized luenberger filter for bounded noise
This paper addresses the problem of distributed state estimation for linear systems with
process and measurement noise, in the case of limited communication data rate, where the …
process and measurement noise, in the case of limited communication data rate, where the …
Distributed experiment design and control for multi-agent systems with gaussian processes
This paper focuses on distributed learning-based control of decentralized multi-agent
systems where the agents' dynamics are modeled by Gaussian Processes (GPs). Two …
systems where the agents' dynamics are modeled by Gaussian Processes (GPs). Two …
Distributed dimensionality reduction fusion Kalman filtering with quantized innovations
This paper is concerned with the distributed fusion Kalman filtering problem for networked
systems with communication constraints. A dimensionality reduction strategy and a uniform …
systems with communication constraints. A dimensionality reduction strategy and a uniform …
Bandwidth limited distributed optimization with applications to networked cyberphysical systems
S Magnússon - 2017 - diva-portal.org
The emerging technology of Cyberphysical systems consists of networked computing,
sensing, and actuator devices used to monitor, connect, and control physical phenomena. In …
sensing, and actuator devices used to monitor, connect, and control physical phenomena. In …
Learning Proximal Operators with Gaussian Process and Adaptive Quantization in Distributed Optimization
A Duarte Vera Tudela - 2024 - repository.lsu.edu
In networks consisting of agents communicating with a central coordinator and working
together to solve a global optimization problem in a distributed manner, the agents are often …
together to solve a global optimization problem in a distributed manner, the agents are often …
Learning Proximal Operators with Gaussian Process and Adaptive Quantization in Distributed Optimization
ADV Tudela - 2024 - search.proquest.com
In networks consisting of agents communicating with a central coordinator and working
together to solve a global optimization problem in a distributed manner, the agents are often …
together to solve a global optimization problem in a distributed manner, the agents are often …