Distributed asynchronous constrained stochastic optimization
K Srivastava, A Nedic - IEEE journal of selected topics in signal …, 2011 - ieeexplore.ieee.org
In this paper, we study two problems which often occur in various applications arising in
wireless sensor networks. These are the problem of reaching an agreement on the value of …
wireless sensor networks. These are the problem of reaching an agreement on the value of …
GADMM: Fast and communication efficient framework for distributed machine learning
When the data is distributed across multiple servers, lowering the communication cost
between the servers (or workers) while solving the distributed learning problem is an …
between the servers (or workers) while solving the distributed learning problem is an …
Quantized subgradient algorithm and data-rate analysis for distributed optimization
In this paper, we consider quantized distributed optimization problems with limited
communication capacity and time-varying communication topology. A distributed quantized …
communication capacity and time-varying communication topology. A distributed quantized …
Noise leads to quasi-consensus of Hegselmann–Krause opinion dynamics
This study aims to provide a theoretical analysis for investigating the consensus behavior of
opinion dynamics in noisy environments. We present how random noises significantly help …
opinion dynamics in noisy environments. We present how random noises significantly help …
Convergence rate of distributed averaging dynamics and optimization in networks
A Nedich - Foundations and Trends® in Systems and …, 2015 - nowpublishers.com
Recent advances in wired and wireless technology lead to the emergence of large-scale
networks such as Internet, wireless mobile ad-hoc networks, swarm robotics, smart-grid, and …
networks such as Internet, wireless mobile ad-hoc networks, swarm robotics, smart-grid, and …
Steady-state analysis of diffusion LMS adaptive networks with noisy links
In this correspondence, we analyze the effects of noisy links on the steady-state
performance of diffusion least-mean-square (LMS) adaptive networks. Using the established …
performance of diffusion least-mean-square (LMS) adaptive networks. Using the established …
On ergodicity, infinite flow, and consensus in random models
We consider the ergodicity and consensus problem for a discrete-time linear dynamic model
driven by random stochastic matrices, which is equivalent to studying these concepts for the …
driven by random stochastic matrices, which is equivalent to studying these concepts for the …
Distributed optimization
A Nedić - Encyclopedia of Systems and Control, 2021 - Springer
The paper provides an overview of the distributed first-order optimization methods for
solving a constrained convex minimization problem, where the objective function is the sum …
solving a constrained convex minimization problem, where the objective function is the sum …
[BOOK][B] Product of random stochastic matrices and distributed averaging
B Touri - 2012 - books.google.com
The thesis deals with averaging dynamics in a multiagent networked system, which is a
main mechanism for diffusing the information over such networks. It arises in a wide range of …
main mechanism for diffusing the information over such networks. It arises in a wide range of …
Noise resilient distributed average consensus over directed graphs
V Khatana, MV Salapaka - IEEE Transactions on Signal and …, 2023 - ieeexplore.ieee.org
Motivated by the needs of resiliency, scalability, and plug-and-play operation, distributed
decision making is becoming increasingly prevalent. The problem of achieving consensus in …
decision making is becoming increasingly prevalent. The problem of achieving consensus in …