Optimization by mean field annealing
Advances in neural information processing systems 1
The nature of statistical learning theory
The nature of statistical learning theory
Semi-supervised support vector machines
Proceedings of the 1998 conference on Advances in neural information processing systems II
Transductive Inference for Text Classification using Support Vector Machines
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
RCV1: A New Benchmark Collection for Text Categorization Research
The Journal of Machine Learning Research
Deterministic annealing for semi-supervised kernel machines
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
Simple, robust, scalable semi-supervised learning via expectation regularization
Proceedings of the 24th international conference on Machine learning
A scalable modular convex solver for regularized risk minimization
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Large scale manifold transduction
Proceedings of the 25th international conference on Machine learning
Optimization Techniques for Semi-Supervised Support Vector Machines
The Journal of Machine Learning Research
Semi-supervised approach to rapid and reliable labeling of large data sets
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Improving Transductive Support Vector Machine by Ensembling
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Automating knowledge capture in the aerospace domain
Proceedings of the fifth international conference on Knowledge capture
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Semi-supervised Discriminant Analysis Based on Dependence Estimation
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
Active learning in partially supervised classification
Proceedings of the 18th ACM conference on Information and knowledge management
Supervised Dual-PLSA for Personalized SMS Filtering
AIRS '09 Proceedings of the 5th Asia Information Retrieval Symposium on Information Retrieval Technology
Bundle Methods for Regularized Risk Minimization
The Journal of Machine Learning Research
Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data
The Journal of Machine Learning Research
Mixture model label propagation
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Semi-supervised Bayesian ARTMAP
Applied Intelligence
Semi-supervised dependency parsing using generalized tri-training
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Robust semi-supervised and ensemble-based methods in word sense disambiguation
IceTAL'10 Proceedings of the 7th international conference on Advances in natural language processing
The effect of semi-supervised learning on parsing long distance dependencies in German and Swedish
IceTAL'10 Proceedings of the 7th international conference on Advances in natural language processing
A fast quasi-Newton method for semi-supervised SVM
Pattern Recognition
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
SMILER: Towards Practical Online Traffic Classification
Proceedings of the 2011 ACM/IEEE Seventh Symposium on Architectures for Networking and Communications Systems
Semi-Supervised Learning with Measure Propagation
The Journal of Machine Learning Research
Latent topic based multi-instance learning method for localized content-based image retrieval
Computers & Mathematics with Applications
Improving Text Classification Accuracy by Training Label Cleaning
ACM Transactions on Information Systems (TOIS)
Large-scale multilabel propagation based on efficient sparse graph construction
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Automatic text classification to support systematic reviews in medicine
Expert Systems with Applications: An International Journal
Convex and scalable weakly labeled SVMs
The Journal of Machine Learning Research
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Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In many information retrieval and data mining applications, linear classifiers are strongly preferred because of their ease of implementation, interpretability and empirical performance. In this work, we present a family of semi-supervised linear support vector classifiers that are designed to handle partially-labeled sparse datasets with possibly very large number of examples and features. At their core, our algorithms employ recently developed modified finite Newton techniques. Our contributions in this paper are as follows: (a) We provide an implementation of Transductive SVM (TSVM) that is significantly more efficient and scalable than currently used dual techniques, for linear classification problems involving large, sparse datasets. (b) We propose a variant of TSVM that involves multiple switching of labels. Experimental results show that this variant provides an order of magnitude further improvement in training efficiency. (c) We present a new algorithm for semi-supervised learning based on a Deterministic Annealing (DA) approach. This algorithm alleviates the problem of local minimum in the TSVM optimization procedure while also being computationally attractive. We conduct an empirical study on several document classification tasks which confirms the value of our methods in large scale semi-supervised settings.