Kernels and Ensembles : Perspectives on Statistical Learning

@inproceedings{Zhu2008KernelsAE,
  title={Kernels and Ensembles : Perspectives on Statistical Learning},
  author={Mu Zhu},
  year={2008}
}
Since their emergence in the 1990s, the support vector machine and the AdaBoost algorithm have spawned a wave of research in statistical machine learning. Much of this new research falls into one of two broad categories: kernel methods and ensemble methods. In this expository article, I discuss the main ideas behind these two types of methods, namely how to transform linear algorithms into nonlinear ones by using kernel functions, and how to make predictions with an ensemble or a collection of… CONTINUE READING
Highly Cited
This paper has 17 citations. REVIEW CITATIONS
12 Citations
13 References
Similar Papers

Similar Papers

Loading similar papers…