Introduction to the theory of neural computation
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Selective Sampling Using the Query by Committee Algorithm
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Combining labeled and unlabeled data with co-training
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Statistical Pattern Recognition: A Review
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Text Classification from Labeled and Unlabeled Documents using EM
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Support vector machine active learning for image retrieval
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Three learning phases for radial-basis-function networks
Neural Networks
Using Unlabelled Data to Train a Multilayer Perceptron
Neural Processing Letters
Constrained K-means Clustering with Background Knowledge
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Semi-supervised Clustering by Seeding
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Transductive Inference for Text Classification using Support Vector Machines
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Enhancing Supervised Learning with Unlabeled Data
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Unlabeled Data Can Degrade Classification Performance of Generative Classifiers
Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference
Active Hidden Markov Models for Information Extraction
IDA '01 Proceedings of the 4th International Conference on Advances in Intelligent Data Analysis
Employing EM and Pool-Based Active Learning for Text Classification
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Learning from Labeled and Unlabeled Data using Graph Mincuts
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Email classification with co-training
CASCON '01 Proceedings of the 2001 conference of the Centre for Advanced Studies on Collaborative research
A Theory of Networks for Approximation and Learning
A Theory of Networks for Approximation and Learning
Using unlabeled data to improve text classification
Using unlabeled data to improve text classification
Support vector machine active learning with applications to text classification
The Journal of Machine Learning Research
Exploitation of Unlabeled Sequences in Hidden Markov Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Selective Sampling for Nearest Neighbor Classifiers
Machine Learning
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ICTAI '04 Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence
Tri-Training: Exploiting Unlabeled Data Using Three Classifiers
IEEE Transactions on Knowledge and Data Engineering
Semi-supervised clustering: probabilistic models, algorithms and experiments
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Fuzzy Labeled Soft Nearest Neighbor Classification with Relevance Learning
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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
An active approach to spoken language processing
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Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
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Semi-supervised learning of compact document representations with deep networks
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Deep learning via semi-supervised embedding
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Optimization Techniques for Semi-Supervised Support Vector Machines
The Journal of Machine Learning Research
Semi-supervised sub-manifold discriminant analysis
Pattern Recognition Letters
Experiments with Supervised Fuzzy LVQ
ANNPR '08 Proceedings of the 3rd IAPR workshop on Artificial Neural Networks in Pattern Recognition
Inter-coder agreement for computational linguistics
Computational Linguistics
Semi-supervised graph clustering: a kernel approach
Machine Learning
Comparison of Neural Classification Algorithms Applied to Land Cover Mapping
Proceedings of the 2009 conference on New Directions in Neural Networks: 18th Italian Workshop on Neural Networks: WIRN 2008
Fishervoice and semi-supervised speaker clustering
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Recognizing body poses using multilinear analysis and semi-supervised learning
Pattern Recognition Letters
Self-training Strategies for Handwriting Word Recognition
ICDM '09 Proceedings of the 9th Industrial Conference on Advances in Data Mining. Applications and Theoretical Aspects
An analysis of active learning strategies for sequence labeling tasks
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Semi-supervised Text Classification Using RBF Networks
IDA '09 Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
Semi-supervised regression with co-training
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Kernel-based metric learning for semi-supervised clustering
Neurocomputing
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Pattern Recognition Letters
Fuzzy-input fuzzy-output one-against-all support vector machines
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
Semi-supervised learning with multilayer perceptron for detecting changes of remote sensing images
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
Multiple-view multiple-learner active learning
Pattern Recognition
Question classification based on co-training style semi-supervised learning
Pattern Recognition Letters
Semi-supervised learning by disagreement
Knowledge and Information Systems
Genetic algorithm–based training for semi-supervised SVM
Neural Computing and Applications
Constraint scores for semi-supervised feature selection: A comparative study
Pattern Recognition Letters
Active deep networks for semi-supervised sentiment classification
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
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COSNet: a cost sensitive neural network for semi-supervised learning in graphs
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part I
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Semi-Supervised kernel clustering with sample-to-cluster weights
PSL'11 Proceedings of the First IAPR TC3 conference on Partially Supervised Learning
Comparison of combined probabilistic connectionist models in a forensic application
PSL'11 Proceedings of the First IAPR TC3 conference on Partially Supervised Learning
A cluster-assumption based batch mode active learning technique
Pattern Recognition Letters
Improve Computer-Aided Diagnosis With Machine Learning Techniques Using Undiagnosed Samples
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
An integrated approach to fuzzy learning vector quantization and fuzzy c-means clustering
IEEE Transactions on Fuzzy Systems
Self-corrective character recognition system
IEEE Transactions on Information Theory
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Soft nearest prototype classification
IEEE Transactions on Neural Networks
Ensemble Methods: Foundations and Algorithms
Ensemble Methods: Foundations and Algorithms
Computer Speech and Language
Contextual and active learning-based affect-sensing from virtual drama improvisation
ACM Transactions on Speech and Language Processing (TSLP)
On instance selection in audio based emotion recognition
ANNPR'12 Proceedings of the 5th INNS IAPR TC 3 GIRPR conference on Artificial Neural Networks in Pattern Recognition
Generalized Query-Based Active Learning to Identify Differentially Methylated Regions in DNA
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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The paper categorizes and reviews the state-of-the-art approaches to the partially supervised learning (PSL) task. Special emphasis is put on the fields of pattern recognition and clustering involving partially (or, weakly) labeled data sets. The major instances of PSL techniques are categorized into the following taxonomy: (i) active learning for training set design, where the learning algorithm has control over the training data; (ii) learning from fuzzy labels, whenever multiple and discordant human experts are involved in the (complex) data labeling process; (iii) semi-supervised learning (SSL) in pattern classification (further sorted out into: self-training, SSL with generative models, semi-supervised support vector machines; SSL with graphs); (iv) SSL in data clustering, using additional constraints to incorporate expert knowledge into the clustering process; (v) PSL in ensembles and learning by disagreement; (vi) PSL in artificial neural networks. In addition to providing the reader with the general background and categorization of the area, the paper aims at pointing out the main issues which are still open, motivating the on-going investigations in PSL research.