A survey on semi-supervised learning

DOI10.1007/s10994-019-05855-6zbMath1441.68215OpenAlexW2984353870MaRDI QIDQ2303675

Holger H. Hoos, Jesper E. van Engelen

Publication date: 4 March 2020

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-019-05855-6

zbMATH Keywords

classificationmachine learningsemi-supervised learning

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Research exposition (monographs, survey articles) pertaining to computer science (68-02)

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Uses Software

• UCI-ml
• KEEL
• Scikit
• AdaBoost.MH
• darch
• word2vec
• TensorFlow
• CIFAR
• PyTorch
• XGBoost
• ImageNet
• Auto-WEKA
• SGTlight
• node2vec
• auto-sklearn
• mixup
• AlexNet
• DeepWalk
• LINE
• PRMLT
• MixMatch
• SemiBoost

Cites Work

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• The self-organizing map
• A decision-theoretic generalization of on-line learning and an application to boosting
• Tree induction for probability-based ranking
• Text classification from labeled and unlabeled documents using EM
• Laplacian twin support vector machine for semi-supervised classification
• A survey on semi-supervised feature selection methods
• Active semi-supervised fuzzy clustering
• Learning from positive and unlabeled examples
• Active Learning
• Graph-Based Semi-Supervised Learning
• Introduction to Semi-Supervised Learning
• Random Forest Construction With Robust Semisupervised Node Splitting
• Learning Theory
• A Fast Learning Algorithm for Deep Belief Nets

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