nips nips2001 nips2001-139 nips2001-139-reference knowledge-graph by maker-knowledge-mining
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Author: Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
Abstract: We consider online learning in a Reproducing Kernel Hilbert Space. Our method is computationally efficient and leads to simple algorithms. In particular we derive update equations for classification, regression, and novelty detection. The inclusion of the -trick allows us to give a robust parameterization. Moreover, unlike in batch learning where the -trick only applies to the -insensitive loss function we are able to derive general trimmed-mean types of estimators such as for Huber’s robust loss. ¡
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