This paper concerns approximate nearest neighbor searching algorithms, which have become increasingly important, especially in high dimensional perception areas such as computer v...
Ting Liu, Andrew W. Moore, Alexander G. Gray, Ke Y...
Linear Discriminant Analysis (LDA) is a popular feature extraction technique in statistical pattern recognition. However, it often suffers from the small sample size problem when ...
In this paper, we consider the problem of unsupervised morphological analysis from a new angle. Past work has endeavored to design unsupervised learning methods which explicitly o...
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 ...
This demonstration program presents the V*-kNN algorithm, an efficient algorithm to process moving k nearest neighbor queries (MkNN). The V*-kNN algorithm is based on a safe-region...
Sarana Nutanong, Rui Zhang, Egemen Tanin, Lars Kul...