Similarity search methods are widely used as kernels in various data mining and machine learning applications including those in computational biology, web search/clustering. Near...
Abstract. We consider approximate nearest neighbor searching in metric spaces of constant doubling dimension. More formally, we are given a set S of n points and an error bound &g...
Sunil Arya, David M. Mount, Antoine Vigneron, Jian...
In high-dimensional classification problems it is infeasible to include enough training samples to cover the class regions densely. Irregularities in the resulting sparse sample d...
We study the use of kernel subspace methods that learn low-dimensional subspace representations for classification tasks. In particular, we propose a new method called kernel weigh...
Abstract. PatchMatch is a fast algorithm for computing dense approximate nearest neighbor correspondences between patches of two image regions [1]. This paper generalizes PatchMatc...