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...
In this paper, we develop a general framework for approximate nearest neighbor queries. We categorize the current approaches for nearest neighbor query processing based on either ...
In this paper we show how the complexity of performing nearest neighbor (NNS) search on a metric space is related to the expansion of the metric space. Given a metric space we loo...
We introduce a new low-distortion embedding of d 2 into O(log n) p (p = 1, 2), called the Fast-Johnson-LindenstraussTransform. The FJLT is faster than standard random projections ...