Optimal Scaling of a Gradient Method for Distributed Resource Allocation

By Lin Xiao, Stephen P. Boyd. 2006

345 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Mechanics, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/c5610e985c32089091ada0a5c24ab4b5aa494ee7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Soomin Lee
2. César A. Uribe
3. Alexander V. Gasnikov
4. Yiguang Hong
5. Alejandro D. Domínguez-García
6. Peng Yi
7. Feng Liu
8. Christoforos N. Hadjicostis

In Computational Mechanics

1. Soomin Lee
2. Alexander V. Gasnikov
3. César A. Uribe
4. Alejandro D. Domínguez-García
5. Peng Yi
6. Feng Liu
7. Christoforos N. Hadjicostis
8. Yiguang Hong

In Computer Networks and Communications

1. Soomin Lee
2. César A. Uribe
3. Yiguang Hong
4. Alexander V. Gasnikov
5. Angelia Nedić
6. Christoforos N. Hadjicostis
7. Peng Yi
8. Alejandro D. Domínguez-García

Citations in the corpus

• A Dual Approach for Optimal Algorithms in Distributed Optimization over Networks (2018, background): “The adoption of distributed optimization algorithms on several fronts of applied and theoretical machine learning, robotics, and resource allocation has increased the attention on such methods in recent years [35, 36, 51, 70, 86].”
• Decentralized optimal dispatch of distributed energy resources (2012, methodology): “The authors of [6] propose a linear-iterative algorithm for optimal resource allocation over a network, where the nodes need to collectively provide a fixed amount of a resource, while minimizing their individual costs; the main differences from our approach is that [6] assumes that: the individual ”
• Distributed dual gradient methods and error bound conditions (2014, neutral): “Also, in comparison with the existing approaches for (DC-OPF) problems we add to the classic quadratic term a weighted logarithmic term, which is used in many resource allocation problem (see e.g. [27]) in order to reduce the absolute risk aversion.”
• Initialization-free distributed algorithms for optimal resource allocation with feasibility constraints and application to economic dispatch of power systems (2015, methodology): “…distributed resource allocation in Ho, Servi, & Suri (1980), some distributed algorithms for resource allocation optimization have been proposed in Xiao & Boyd (2006), Lakshmanan & Farias (2008), Necoara, Nesterov, & Glineur (2011), Ghadimi, Shames, & Johansson (2013), and Beck, Nedic, Ozdaglar,…”