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Subderivative

Known as: Subdifferential, Subgradient 
In mathematics, the subderivative, subgradient, and subdifferential generalize the derivative to functions which are not differentiable. The… Expand
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Highly Cited
2015
Highly Cited
2015
We consider distributed optimization by a collection of nodes, each having access to its own convex function, whose collective… Expand
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Highly Cited
2012
Highly Cited
2012
The goal of decentralized optimization over a network is to optimize a global objective formed by a sum of local (possibly… Expand
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Highly Cited
2010
Highly Cited
2010
We consider a distributed multi-agent network system where the goal is to minimize a sum of convex objective functions of the… Expand
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Highly Cited
2010
Highly Cited
2010
We present distributed algorithms that can be used by multiple agents to align their estimates with a particular value over a… Expand
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Highly Cited
2008
Highly Cited
2008
1 Introduction 2 Going variational 2.1 Griffith's theory 2.2 The 1-homogeneous case - A variational equivalence 2.3 Smoothness… Expand
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Highly Cited
2007
Highly Cited
2007
This note analyzes the stability properties of a group of mobile agents that align their velocity vectors, and stabilize their… Expand
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Highly Cited
2004
Highly Cited
2004
Wireless sensor networks are capable of collecting an enormous amount of data over space and time. Often, the ultimate objective… Expand
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Highly Cited
2002
Highly Cited
2002
Price forecasting is becoming increasingly relevant to producers and consumers in the new competitive electric power markets… Expand
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Highly Cited
1976
Highly Cited
1976
For the problem of minimizing a lower semicontinuous proper convex function f on a Hilbert space, the proximal point algorithm in… Expand
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Highly Cited
1974
Highly Cited
1974
The “relaxation” procedure introduced by Held and Karp for approximately solving a large linear programming problem related to… Expand
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