Semi-supervised learning

Known as: SSL, Semi supervised learning, Semisupervised learning 
Semi-supervised learning is a class of supervised learning tasks and techniques that also make use of unlabeled data for training – typically a small… (More)
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Active learning (machine learning)Classic monolingual word-sense disambiguationCo-trainingConcept learning
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Machine learning

Papers overview

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Review
2017
Review
2017
Variational Autoencoder for Semi-Supervised Text Classification
Although semi-supervised variational autoencoder (SemiVAE) works in image classification task, it fails in text classification… (More)
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Highly Cited
2015
Highly Cited
2015
Semi-supervised Learning with Ladder Networks
We combine supervised learning with unsupervised learning in deep neural networks. The proposed model is trained to… (More)
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Highly Cited
2014
Highly Cited
2014
Semi-Supervised Learning with Deep Generative Models
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
Semi-Supervised Learning
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
2010
Highly Cited
2010
Coupled semi-supervised learning for information extraction
We consider the problem of semi-supervised learning to extract categories (e.g., academic fields, athletes) and relations (e.g… (More)
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Highly Cited
2009
Highly Cited
2009
SemiBoost: Boosting for Semi-Supervised Learning
Semi-supervised learning has attracted a significant amount of attention in pattern recognition and machine learning. Most… (More)
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Highly Cited
2009
Highly Cited
2009
Semi-supervised Learning by Sparse Representation
In this paper, we present a novel semi-supervised learning framework based on `1 graph. The `1 graph is motivated by that each… (More)
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Highly Cited
2005
Highly Cited
2005
Semi-Supervised Learning for Natural Language
Statistical supervised learning techniques have been successful for many natural language processing tasks, but they require… (More)
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Highly Cited
2004
Highly Cited
2004
Semi-Supervised Learning on Riemannian Manifolds
We consider the general problem of utilizing both labeled and unlabeled data to improve classification accuracy. Under the… (More)
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Highly Cited
2002
Highly Cited
2002
Cluster Kernels for Semi-Supervised Learning
We propose a framework to incorporate unlabeled data in kernel classifier, based on the idea that two points in the same cluster… (More)
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