Abstract. Nearest neighbor search has a wide variety of applications. Unfortunately, the majority of search methods do not scale well with dimensionality. Recent efforts have been ...
Naive Bayes Nearest Neighbor (NBNN) has recently been proposed as a powerful, non-parametric approach for object classification, that manages to achieve remarkably good results t...
Tinne Tuytelaars, Mario Fritz, Kate Saenko, Trevor...
Given a metric space (X, dX), c ≥ 1, r > 0, and p, q ∈ [0, 1], a distribution over mappings H : X → N is called a (r, cr, p, q)-sensitive hash family if any two points in...
In this paper, we propose a novel formulation for distance-based outliers that is based on the distance of a point from its kth nearest neighbor. We rank each point on the basis o...
Abstract. The expressiveness of a lot of image analysis algorithms depends on the question whether shape information is preserved during digitization. Most existing approaches to a...