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Review

2018

Review

2018

In decentralized optimization, nodes cooperate to minimize an overall objective function that is the sum (or average) of per-node… Expand

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Review

2018

Review

2018

Low-rank modeling plays a pivotal role in signal processing and machine learning, with applications ranging from collaborative… Expand

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Review

2018

Review

2018

Cloud radio access network (C-RAN) has emerged as a potential candidate of the next generation access network technology to… Expand

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Highly Cited

2012

Highly Cited

2012

Suppose that one observes an incomplete subset of entries selected from a low-rank matrix. When is it possible to complete the… Expand

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Highly Cited

2009

Highly Cited

2009

We consider a problem of considerable practical interest: the recovery of a data matrix from a sampling of its entries. Suppose… Expand

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Highly Cited

2009

Highly Cited

2009

We consider the problem of choosing a set of k sensor measurements, from a set of m possible or potential sensor measurements… Expand

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Highly Cited

2007

Highly Cited

2007

Abstract
In an online convex optimization problem a decision-maker makes a sequence of decisions, i.e., chooses a sequence of… Expand

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Highly Cited

2006

Highly Cited

2006

Convex optimization problems arise frequently in many different fields. A comprehensive introduction to the subject, this book… Expand

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Highly Cited

2004

Highly Cited

2004

It was in the middle of the 1980s, when the seminal paper by Kar markar opened a new epoch in nonlinear optimization. The… Expand

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Highly Cited

1998

Highly Cited

1998

We study convex optimization problems for which the data is not specified exactly and it is only known to belong to a given… Expand

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