We present a new Bi-level LSH algorithm to perform approximate k-nearest neighbor search in high dimensional spaces. Our formulation is based on a two-level scheme. In the first ...
Abstract. We introduce a nonparametric model for sensitivity estimation which relies on generating points similar to the prediction point using its k nearest neighbors. Unlike most...
Recently, hashing based Approximate Nearest Neighbor (ANN) techniques have been attracting lots of attention in computer vision. The data-dependent hashing methods, e.g., Spectral...
Hao Xu, Jingdong Wang, Zhu Li, Gang Zeng, Shipeng ...
: The k nearest neighbor classification (k-NN) is a very simple and popular method for classification. However, it suffers from a major drawback, it assumes constant local class po...
Coherency Sensitive Hashing (CSH) extends Locality Sensitivity Hashing (LSH) and PatchMatch to quickly find matching patches between two images. LSH relies on hashing, which maps...