The nature of statistical learning theory
The nature of statistical learning theory
Machine Learning
The Relaxed Online Maximum Margin Algorithm
Machine Learning
The Kernel-Adatron Algorithm: A Fast and Simple Learning Procedure for Support Vector Machines
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Duality and Geometry in SVM Classifiers
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
A new approximate maximal margin classification algorithm
The Journal of Machine Learning Research
Ultraconservative online algorithms for multiclass problems
The Journal of Machine Learning Research
Fast Kernel Classifiers with Online and Active Learning
The Journal of Machine Learning Research
Solving multiclass support vector machines with LaRank
Proceedings of the 24th international conference on Machine learning
Confidence-weighted linear classification
Proceedings of the 25th international conference on Machine learning
Accelerating kernel perceptron learning
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Fast and Scalable Local Kernel Machines
The Journal of Machine Learning Research
Distribution-aware online classifiers
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Confidence-weighted linear classification for text categorization
The Journal of Machine Learning Research
Live and learn from mistakes: A lightweight system for document classification
Information Processing and Management: an International Journal
Adaptive regularization of weight vectors
Machine Learning
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We propose a novel online kernel classifier algorithm that converges to the Hard Margin SVM solution. The same update rule is used to both add and remove support vectors from the current classifier. Experiments suggest that this algorithm matches the SVM accuracies after a single pass over the training examples. This algorithm is attractive when one seeks a competitive classifier with large datasets and limited computing resources.