Wasserstein Exponential Kernels

5 Feb 2020Henri De PlaenMichaël FanuelJohan A. K. Suykens

In the context of kernel methods, the similarity between data points is encoded by the kernel function which is often defined thanks to the Euclidean distance, a common example being the squared exponential kernel. Recently, other distances relying on optimal transport theory - such as the Wasserstein distance between probability distributions - have shown their practical relevance for different machine learning techniques... (read more)

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