When does a digraph admit a doubly stochastic adjacency matrix?
By Bahman Gharesifard, Jorge Cortés. 2010
93 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Public Health, Environmental and Occupational Health
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Angelia Nedić
- Michael G. Rabbat
- Konstantinos I. Tsianos
- Gesualdo Scutari
- Sean F. Lawlor
- Hanlin Tang
- Ji Liu
- Alexander Olshevsky
In Public Health, Environmental and Occupational Health
- Gesualdo Scutari
- Christoforos N. Hadjicostis
- Konstantinos I. Tsianos
- Michael G. Rabbat
- Hanlin Tang
- Ji Liu
- Ying Sun
Citations in the corpus
- Central Server Free Federated Learning over Single-sided Trust Social Networks (2019, background): “Such a requirement is quite restrictive, because not all networks admit a doubly stochastic matrix (Gharesifard and Cortés 2010), and relinquishing double stochasticity can introduce bias in optimization (Ram et al.”
- Push-Sum Distributed Dual Averaging for convex optimization (2012, background): “For example, not all (directed) networks admit a doubly stochastic matrix [6].”
- Consensus-based distributed optimization: Practical issues and applications in large-scale machine learning (2012, background): “Finally, there might be cases where a directed network does not admit a doubly stochastic consensus matrix [26].”
- Distributed dual averaging for convex optimization under communication delays (2012, unknown): “Moreover, as explained in [9] for some network topologies it may not be possible to use a doubly stochastic consensus protocol.”
- Distributed Matrix Scaling and Application to Average Consensus in Directed Graphs (2013, background): “One of the early motivations for this problem was the desire to start from the stochastic matrix of a Markov chain and obtain a scaled version of it that is doubly stochastic and adheres to the sparsity structure of the original one [17].”
- Distributed nonconvex constrained optimization over time-varying digraphs (2018, background): “When the graph is directed, doublestochastic weight matrices compliant to the graph might not exist or are not easy to be constructed in a distributed way [20].”