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Supervised learning

Known as: Fully-supervised machine learning, Supervised Machine Learning, Supervised classification 
Supervised learning is the machine learning task of inferring a function from labeled training data. The training data consist of a set of training… Expand
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2014
Highly Cited
2014
The ever-increasing size of modern data sets combined with the difficulty of obtaining label information has made semi-supervised… Expand
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Highly Cited
2009
Highly Cited
2009
Semi-supervised learning is a learning paradigm concerned with the study of how computers and natural systems such as humans… Expand
Highly Cited
2008
Highly Cited
2008
It is now well established that sparse signal models are well suited for restoration tasks and can be effectively learned from… Expand
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Review
2006
Review
2006
In the field of machine learning, semi-supervised learning (SSL) occupies the middle ground, between supervised learning (in… Expand
Highly Cited
2006
Highly Cited
2006
A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical… Expand
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Highly Cited
2006
Highly Cited
2006
This chapter contains sections titled: Supervised, Unsupervised, and Semi-Supervised Learning, When Can Semi-Supervised Learning… Expand
Highly Cited
2006
Highly Cited
2006
Social network analysis has attracted much attention in recent years. Link prediction is a key research directions within this… Expand
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Highly Cited
2004
Highly Cited
2004
We consider the semi-supervised learning problem, where a decision rule is to be learned from labeled and unlabeled data. In this… Expand
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Highly Cited
2003
Highly Cited
2003
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data… Expand
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Highly Cited
1993
Highly Cited
1993
A supervised learning algorithm (Scaled Conjugate Gradient, SCG) is introduced. The performance of SCG is benchmarked against… Expand
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