Learning from Few Samples: Transformation-Invariant SVMs with Composition and Locality at Multiple Scales

Particularly important is the ability to incorporate domain knowledge of invariances, e.g., translational invariance of images. Kernels based on the maximum similarity over a group of transformations are not generally positive definite. Perhaps it is for this reason that they have not been studied theoretically.