In this paper, we consider a smoothing kernelbased classification rule and propose an algorithm for optimizing the performance of the rule by learning the bandwidth of the smoothi...
Bharath K. Sriperumbudur, Omer A. Lang, Gert R. G....
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Abstract— The paper presents an efficient construction algorithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model gener...
Recent work has introduced Boolean kernels with which one can learn linear threshold functions over a feature space containing all conjunctions of length up to k (for any 1 ≤ k ...
A kernel over the Boolean domain is said to be reflection-invariant, if its value does not change when we flip the same bit in both arguments. (Many popular kernels have this prop...
Thorsten Doliwa, Michael Kallweit, Hans-Ulrich Sim...