A Universal Kernel for Learning Regular Languages
Mining and Learning with Graphs (MLG), 2007
Abstract
We give a universal kernel that renders all the regular languages linearly separable. We are not able to compute this kernel efficiently and conjecture that it is intractable, but we do have an efficient -approximation.
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