A method is described which, like the kernel trick in support vector machines (SVMs), lets us generalize distance-based algorithms to operate in feature spaces, usually nonlinearl...
Tasks of data mining and information retrieval depend on a good distance function for measuring similarity between data instances. The most effective distance function must be for...
Tasks of information retrieval depend on a good distance function for measuring similarity between data instances. The most effective distance function must be formulated in a con...
In this paper, we present a kernel trick embedded Gaussian Mixture Model (GMM), called kernel GMM. The basic idea is to embed kernel trick into EM algorithm and deduce a parameter ...
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...