Rylan Schaeffer

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Kernel Papers


Kernel Methods

At a high level, kernel methods are a machine learning approach that works by first transforming any data (images, songs, etc.) into (possibly infinite dimensional) feature spaces, computing the pairwise similarity of each datum through inner products, and then fitting a simple model (i.e. a linear readout) from the feature space.

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