Subderivative

Known as: Subdifferential, Subgradient 
In mathematics, the subderivative, subgradient, and subdifferential generalize the derivative to functions which are not differentiable. The… (More)
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Topic mentions per year

Topic mentions per year

1965-2017
05010015019652017

Papers overview

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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… (More)
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Highly Cited
2010
Highly Cited
2010
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in… (More)
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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… (More)
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Highly Cited
2009
Highly Cited
2009
We study a distributed computation model for optimizing a sum of convex objective functions corresponding to multiple agents. For… (More)
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Highly Cited
2009
Highly Cited
2009
In this paper we consider optimization problems where the objective function is given in a form of the expectation. A basic… (More)
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Highly Cited
2009
Highly Cited
2009
In this paper we present a new approach for constructing subgradient schemes for different types of nonsmooth problems with… (More)
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Highly Cited
2006
Highly Cited
2006
Motivated by applications to sensor, peer-to-peer, and ad hoc networks, we study distributed algorithms, also known as gossip… (More)
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Highly Cited
2005
Highly Cited
2005
Motivated by applications to sensor, peer-to-peer and ad hoc networks, we study distributed asynchronous algorithms, also known… (More)
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Highly Cited
2004
Highly Cited
2004
We consider the problem of !nding a linear iteration that yields distributed averaging consensus over a network, i.e., that… (More)
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Highly Cited
2001
Highly Cited
2001
We consider a class of subgradient methods for minimizing a convex function that consists of the sum of a large number of… (More)
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