A tutorial on modeling and analysis of dynamic social networks. Part II

AV Proskurnikov, R Tempo - Annual Reviews in Control, 2018‏ - Elsevier
Recent years have witnessed a significant trend towards filling the gap between Social
Network Analysis (SNA) and control theory. This trend was enabled by the introduction of …

Communication-efficient distributed deep learning: A comprehensive survey

Z Tang, S Shi, W Wang, B Li, X Chu - arxiv preprint arxiv:2003.06307, 2020‏ - arxiv.org
Distributed deep learning (DL) has become prevalent in recent years to reduce training time
by leveraging multiple computing devices (eg, GPUs/TPUs) due to larger models and …

Can decentralized algorithms outperform centralized algorithms? a case study for decentralized parallel stochastic gradient descent

X Lian, C Zhang, H Zhang, CJ Hsieh… - Advances in neural …, 2017‏ - proceedings.neurips.cc
Most distributed machine learning systems nowadays, including TensorFlow and CNTK, are
built in a centralized fashion. One bottleneck of centralized algorithms lies on high …

[كتاب][B] Lectures on network systems

F Bullo, J Cortés, F Dörfler, S Martínez - 2018‏ - zdocs.mx
Topics These lecture notes are intended primarily for graduate students interested in
network systems, distributed algorithms, and cooperative control. The objective is to answer …

Asynchronous decentralized parallel stochastic gradient descent

X Lian, W Zhang, C Zhang, J Liu - … Conference on Machine …, 2018‏ - proceedings.mlr.press
Most commonly used distributed machine learning systems are either synchronous or
centralized asynchronous. Synchronous algorithms like AllReduce-SGD perform poorly in a …

Graph theoretic methods in multiagent networks

M Mesbahi, M Egerstedt - 2010‏ - torrossa.com
“I don't want to achieve immortality through my work... I want to achieve it through not dying.”—
Woody Allen The emergence of (relatively) cheap sensing and actuation nodes, capable of …

Heterophilious dynamics enhances consensus

S Motsch, E Tadmor - SIAM review, 2014‏ - SIAM
We review a general class of models for self-organized dynamics based on alignment. The
dynamics of such systems is governed solely by interactions among individuals or “agents,” …

Opinion dynamics and learning in social networks

D Acemoglu, A Ozdaglar - Dynamic Games and Applications, 2011‏ - Springer
We provide an overview of recent research on belief and opinion dynamics in social
networks. We discuss both Bayesian and non-Bayesian models of social learning and focus …

Gossip algorithms for distributed signal processing

AG Dimakis, S Kar, JMF Moura… - Proceedings of the …, 2010‏ - ieeexplore.ieee.org
Gossip algorithms are attractive for in-network processing in sensor networks because they
do not require any specialized routing, there is no bottleneck or single point of failure, and …

Opinion dynamics in social networks with stubborn agents: Equilibrium and convergence rate

J Ghaderi, R Srikant - Automatica, 2014‏ - Elsevier
The process by which new ideas, innovations, and behaviors spread through a large social
network can be thought of as a networked interaction game: Each agent obtains information …