In this paper we study how to improve nearest neighbor classification by learning a Mahalanobis distance metric. We build on a recently proposed framework for distance metric lear...
The reverse k-nearest neighbor (RkNN) problem, i.e. finding all objects in a data set the k-nearest neighbors of which include a specified query object, is a generalization of the...
We present a novel expert-model of Query-Driven Locally Adaptive (QDLA) Fisher faces for robust face recognition. For each query face, the proposed method first fits local Fisher ...
Yun Fu, Junsong Yuan, Zhu Li, Thomas S. Huang, Yin...
Abstract—Nearest Neighbour search is a widely used technique in Pattern Recognition. In order to speed up the search many indexing techniques have been proposed. However, most of...
In this paper we give approximation algorithms for several proximity problems in high dimensional spaces. In particular, we give the rst Las Vegas data structure for (1 + )-neares...