The nature of statistical learning theory
The nature of statistical learning theory
Support vector domain description
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
One-class svms for document classification
The Journal of Machine Learning Research
Convergence of alternating optimization
Neural, Parallel & Scientific Computations
Robust Real-Time Face Detection
International Journal of Computer Vision
Computer aided detection via asymmetric cascade of sparse hyperplane classifiers
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
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In this study we introduce a novel algorithm for learning a polyhedron to describe the target class. The proposed approach takes advantage of the limited subclass information made available for the negative samples and jointly optimizes multiple hyperplane classifiers each of which is designed to classify positive samples from a subclass of the negative samples. The flat faces of the polyhedron provides robustness whereas multiple faces contributes to the flexibility required to deal with complex datasets. Apart from improving the prediction accuracy of the system, the proposed polyhedral classifier also provides run-time speedups as a by-product when executed in a cascaded framework in real-time. We evaluate the performance of the proposed technique on a real-world Colon dataset both in terms of prediction accuracy and online execution speed.