The "nearest neighbor" relation, or more generally the "k nearest neighbors" relation, defined for a set of points in a metric space, has found many uses in co...
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...
There are many nearest neighbor algorithms tailormade for ICP, but most of them require special input data like range images or triangle meshes. We focus on efficient nearest nei...
Nearest neighbor (NN) searches represent an important class of queries in geographic information systems (GIS). Most nearest neighbor algorithms rely on static distance informatio...
Wei-Shinn Ku, Roger Zimmermann, Haojun Wang, Chi-N...
Motivation: Net Nearest Neighbor Analysis (NNNA) measures a previously unexamined aspect of dinucleotide frequency--the non-compensated, non-repetitive dinucleotides in a sequence...