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… (More)
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Papers overview

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Review
2017
Review
2017
Although semi-supervised variational autoencoder (SemiVAE) works in image classification task, it fails in text classification… (More)
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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… (More)
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Highly Cited
2010
Highly Cited
2010
All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including… (More)
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Highly Cited
2006
Highly Cited
2006
A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical… (More)
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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… (More)
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Highly Cited
2003
Highly Cited
2003
The goal of supervised learning is to infer a functional mapping based on a set of training examples. To achieve good… (More)
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Highly Cited
2000
Highly Cited
2000
In many practical learning scenarios, there is a small amount of labeled data along with a large pool of unlabeled data. Many… (More)
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Highly Cited
1993
Highly Cited
1993
A supervised learning algorithm (Scaled Conjugate Gradient, SCG) with superlinear convergence rate is introduced. The algorithm… (More)
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Highly Cited
1992
Highly Cited
1992
Internal models of the environment have an important role to play in adaptive systems in general and are of particular importance… (More)
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Highly Cited
1992
Highly Cited
1992
A neural network architecture is introduced for incremental supervised learning of recognition categories and multidimensional… (More)
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