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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… Expand
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2020
Review
2020
This work considers the question of how convenient access to copious data impacts our ability to learn causal effects and… Expand
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Review
2019
Review
2019
The quest of `can machines think' and `can machines do what human do' are quests that drive the development of artificial… Expand
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Review
2018
Review
2018
As a new classification platform, deep learning has recently received increasing attention from researchers and has been… Expand
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Review
2018
Review
2018
Deep learning has been shown to be successful in a number of domains, ranging from acoustics, images, to natural language… Expand
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Review
2017
Review
2017
Graph-structured data such as social networks, functional brain networks, gene regulatory networks, communications networks have… Expand
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Highly Cited
2017
Highly Cited
2017
We present a scalable approach for semi-supervised learning on graph-structured data that is based on an efficient variant of… Expand
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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… 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
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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
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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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