Metric Learning with Multiple Kernels

@inproceedings{Wang2011MetricLW,
  title={Metric Learning with Multiple Kernels},
  author={Jun Wang and Huyen Do and Adam Woznica and Alexandros Kalousis},
  booktitle={NIPS},
  year={2011}
}
Metric learning has become a very active research field. The most popular representative–Mahalanobis metric learning–can be seen as learning a linear transformation and then computing the Euclidean metric in the transformed space. Since a linear transformation might not always be appropriate for a given learning problem, kernelized versions of various metric learning algorithms exist. However, the problem then becomes finding the appropriate kernel function. Multiple kernel learning addresses… CONTINUE READING

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