FAQ

Optimization problem

Known as: NP optimization problem, Optimal solution, Optimal value 
In mathematics and computer science, an optimization problem is the problem of finding the best solution from all feasible solutions. Optimization… (More)
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Topic mentions per year

1951-2018
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Related topics

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Canadian traveller problemClique problemComparison of optimization softwareCompetitive programming
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Related mentions per year

Related mentions per year

1937-2018
19401960198020002020
Optimization problem
Mathematical optimization
Computational complexity theory
Computer science
Evolutionary algorithm
Convex optimization

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2018
Review
2018
A Survey on Learning to Hash
Nearest neighbor search is a problem of finding the data points from the database such that the distances from them to the query… (More)
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Review
2016
Review
2016
Concrete Problems in AI Safety
Rapid progress in machine learning and artificial intelligence (AI) has brought increasing attention to the potential impacts of… (More)
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Highly Cited
2010
Highly Cited
2010
Constrained Consensus and Optimization in Multi-Agent Networks
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
Distributed Subgradient Methods for Multi-Agent Optimization
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
2006
Highly Cited
2006
Dual methods for nonconvex spectrum optimization of multicarrier systems
The design and optimization of multicarrier communications systems often involve a maximization of the total throughput subject… (More)
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Highly Cited
2004
Highly Cited
2004
Robust Optimization
We propose new methodologies in robust optimization that promise greater tractability, both theoretically and practically than… (More)
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Highly Cited
2001
Highly Cited
2001
SVMTorch: Support Vector Machines for Large-Scale Regression Problems
Support Vector Machines (SVMs) for regression problems are trained by solving a quadratic optimization problem which needs on the… (More)
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Highly Cited
2000
Highly Cited
2000
Fast Training of Support Vector Machines using Sequential Minimal Optimization
This chapter describes a new algorithm for training Support Vector Machines: Sequential Minimal Optimization, or SMO. Training a… (More)
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Highly Cited
1998
Highly Cited
1998
Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones
SeDuMi is an add-on for MATLAB, that lets you solve optimization problems with linear, quadratic and semideeniteness constraints… (More)
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Highly Cited
1997
Highly Cited
1997
No free lunch theorems for optimization
A framework is developed to explore the connection between e ective optimization algorithms and the problems they are solving A… (More)
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