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Local optimum

Known as: Local optima, Local optimality, Locally optimal 
In applied mathematics and computer science, a local optimum of an optimization problem is a solution that is optimal (either maximal or minimal… Expand
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Related topics

Related topics

26 relations
AlgorithmAutomatic label placementBroyden–Fletcher–Goldfarb–Shanno algorithmCluster analysis
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Broader (1)

Mathematical optimization

Papers overview

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Highly Cited
2009
Highly Cited
2009
On the local optimality of LambdaRank
A machine learning approach to learning to rank trains a model to optimize a target evaluation measure with repect to training… Expand
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Highly Cited
2009
Highly Cited
2009
Learning from ambiguously labeled images
In many image and video collections, we have access only to partially labeled data. For example, personal photo collections often… Expand
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Highly Cited
2006
Highly Cited
2006
Optimal and Near-Optimal Signal Detection in Snapping Shrimp Dominated Ambient Noise
The optimal detection of signals requires detailed knowledge of the noise statistics. In many applications, the assumption of… Expand
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Highly Cited
2004
Highly Cited
2004
Pareto Local Optimum Sets in the Biobjective Traveling Salesman Problem: An Experimental Study
In this article, we study Pareto local optimum sets for the biobjective Traveling Salesman Problem applying straightforward… Expand
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Highly Cited
2002
Highly Cited
2002
On optimal traffic grooming in WDM rings
We consider the problem of designing a virtual topology to minimize electronic routing, that is, grooming traffic, in wavelength… Expand
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Highly Cited
2001
Highly Cited
2001
Toward the Optimal Preconditioned Eigensolver: Locally Optimal Block Preconditioned Conjugate Gradient Method
We describe new algorithms of the locally optimal block preconditioned conjugate gradient (LOBPCG) method for symmetric… Expand
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Highly Cited
2001
Highly Cited
2001
The Trade-Off between Efficiency and Learning in Interorganizational Relationships for Product Development
This paper analyzes the performance implications of interorganizational relationships in the development of technological… Expand
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Highly Cited
1999
Highly Cited
1999
Policy Gradient Methods for Reinforcement Learning with Function Approximation
Function approximation is essential to reinforcement learning, but the standard approach of approximating a value function and… Expand
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Highly Cited
1997
Highly Cited
1997
Tradeoff between source and channel coding
A problem in the transmission of analog information across a noisy discrete channel is the choice of channel code rate that… Expand
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Highly Cited
1985
Highly Cited
1985
How easy is local search?
We investigate the complexity of finding locally optimal solutions to NP-hard combinatorial optimization problems. Local… Expand
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