Support Vector Machines (SVMs) and related kernel methods have become increasingly popular tools for data mining tasks such as classification, regression, and novelty detection. T...
Due to its wide applicability, the problem of semi-supervised classification is attracting increasing attention in machine learning. Semi-Supervised Support Vector Machines (S3VMs...
Olivier Chapelle, Vikas Sindhwani, S. Sathiya Keer...
Extracting sentences that contain important information from a document is a form of text summarization. The technique is the key to the automatic generation of summaries similar ...
Support Vector Machine (SVM) has been spotlighted in the machine learning community thanks to its theoretical soundness and practical performance. When applied to a large data set...
Support vector machines (SVMs) are regularly used for classification of unbalanced data by weighting more heavily the error contribution from the rare class. This heuristic techn...