Structured large margin machines: sensitive to data distributions

Abstract

This paper proposes a new large margin classifier—the structured large margin machine (SLMM)—that is sensitive to the structure of the data distribution. The SLMM approach incorporates the merits of “structured” learning models, such as radial basis function networks and Gaussian mixture models, with the advantages of “unstructured” large margin learning… (More)
DOI: 10.1007/s10994-007-5015-9

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@article{Yeung2007StructuredLM, title={Structured large margin machines: sensitive to data distributions}, author={Daniel S. Yeung and Defeng Wang and Eric C. C. Tsang and Xizhao Wang}, journal={Machine Learning}, year={2007}, volume={68}, pages={171-200} }