Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Semi-supervised support vector machines
Proceedings of the 1998 conference on Advances in neural information processing systems II
Choosing Multiple Parameters for Support Vector Machines
Machine Learning
Transductive Inference for Text Classification using Support Vector Machines
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Neural Computation
Learning with progressive transductive support vector machine
Pattern Recognition Letters
Beyond the point cloud: from transductive to semi-supervised learning
ICML '05 Proceedings of the 22nd international conference on Machine learning
An evolutionary approach to Transduction in Support Vector Machines
HIS '05 Proceedings of the Fifth International Conference on Hybrid Intelligent Systems
A continuation method for semi-supervised SVMs
ICML '06 Proceedings of the 23rd international conference on Machine learning
Deterministic annealing for semi-supervised kernel machines
ICML '06 Proceedings of the 23rd international conference on Machine learning
Large scale semi-supervised linear SVMs
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Training a Support Vector Machine in the Primal
Neural Computation
The Journal of Machine Learning Research
Nonsmooth Optimization Techniques for Semisupervised Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Semi-Supervised Learning
Improving Transductive Support Vector Machine by Ensembling
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Semi-supervised learning using label mean
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Kernel Based Regularized Multiple Criteria Linear Programming Model
ICCS 2009 Proceedings of the 9th International Conference on Computational Science
Is unlabeled data suitable for multiclass SVM-based web page classification?
SemiSupLearn '09 Proceedings of the NAACL HLT 2009 Workshop on Semi-Supervised Learning for Natural Language Processing
An active learning approach for segmenting human activity datasets
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Help-training semi-supervised LS-SVM
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Outer approximation algorithms for canonical DC problems
Journal of Global Optimization
Discriminative semi-supervised feature selection via manifold regularization
IEEE Transactions on Neural Networks
Semi-supervised Bayesian ARTMAP
Applied Intelligence
An effective procedure exploiting unlabeled data to build monitoring system
Expert Systems with Applications: An International Journal
Support Vector Machines with the Ramp Loss and the Hard Margin Loss
Operations Research
Help-Training for semi-supervised support vector machines
Pattern Recognition
Laplacian Support Vector Machines Trained in the Primal
The Journal of Machine Learning Research
Expert Systems with Applications: An International Journal
Semi-supervised SVMs for classification with unknown class proportions and a small labeled dataset
Proceedings of the 20th ACM international conference on Information and knowledge management
Expert Systems with Applications: An International Journal
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Manifold-Regularized minimax probability machine
PSL'11 Proceedings of the First IAPR TC3 conference on Partially Supervised Learning
Review: Supervised classification and mathematical optimization
Computers and Operations Research
Analysis of presence-only data via semi-supervised learning approaches
Computational Statistics & Data Analysis
A novel inductive semi-supervised SVM with graph-based self-training
IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Journal of Information Science
Semi-supervised learning using greedy max-cut
The Journal of Machine Learning Research
A second order cone programming approach for semi-supervised learning
Pattern Recognition
DCA based algorithms for feature selection in semi-supervised support vector machines
MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition
A class of semi-supervised support vector machines by DC programming
Advances in Data Analysis and Classification
Pattern classification and clustering: A review of partially supervised learning approaches
Pattern Recognition Letters
Laplacian minimax probability machine
Pattern Recognition Letters
Convex and scalable weakly labeled SVMs
The Journal of Machine Learning Research
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Due to its wide applicability, the problem of semi-supervised classification is attracting increasing attention in machine learning. Semi-Supervised Support Vector Machines (S3VMs) are based on applying the margin maximization principle to both labeled and unlabeled examples. Unlike SVMs, their formulation leads to a non-convex optimization problem. A suite of algorithms have recently been proposed for solving S3VMs. This paper reviews key ideas in this literature. The performance and behavior of various S3VMs algorithms is studied together, under a common experimental setting.