Hashing, which tries to learn similarity-preserving binary codes for data representation, has been widely used for efficient nearest neighbor search in massive databases due to i...
Many high-profile applications pose high-dimensional nearest-neighbor search problems. Yet, it still remains difficult to achieve fast query times for state-of-the-art approache...
A new data structure for efficient similarity search in very large datasets of high-dimensional vectors is introduced. This structure called the inverted multi-index generalizes ...
We propose an efficient algorithm to find the exact nearest neighbor based on the Euclidean distance for largescale computer vision problems. We embed data points nonlinearly on...
There has been growing interest in mapping image data onto compact binary codes for fast near neighbor search in vision applications. Although binary codes are motivated by their ...
Mohammad Emtiyaz Norouzi, Ali Punjani, David J. Fl...
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 ...
Applications like multimedia retrieval require efficient support for similarity search on large data collections. Yet, nearest neighbor search is a difficult problem in high dimen...
Arjen P. de Vries, Nikos Mamoulis, Niels Nes, Mart...