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STOC
2006
ACM
244views Algorithms» more  STOC 2006»
14 years 7 months ago
Approximate nearest neighbors and the fast Johnson-Lindenstrauss transform
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 ...
Nir Ailon, Bernard Chazelle
ICASSP
2010
IEEE
13 years 7 months ago
Searching with expectations
Handling large amounts of data, such as large image databases, requires the use of approximate nearest neighbor search techniques. Recently, Hamming embedding methods such as spec...
Harsimrat Sandhawalia, Herve Jegou
ACIVS
2006
Springer
14 years 1 months ago
A Comparison of Nearest Neighbor Search Algorithms for Generic Object Recognition
The nearest neighbor (NN) classifier is well suited for generic object recognition. However, it requires storing the complete training data, and classification time is linear in ...
Ferid Bajramovic, Frank Mattern, Nicholas Butko, J...
ICPR
2002
IEEE
14 years 8 months ago
Metric-Based Shape Retrieval in Large Databases
This paper examines the problem of database organization and retrieval based on computing metric pairwise distances. A low-dimensional Euclidean approximation of a high-dimensiona...
Thomas B. Sebastian, Benjamin B. Kimia
ISMIR
2005
Springer
154views Music» more  ISMIR 2005»
14 years 1 months ago
Exploiting the Tradeoff Between Precision and Cpu-Time to Speed Up Nearest Neighbor Search
We describe a recursive algorithm to quickly compute the N nearest neighbors according to a similarity measure in a metric space. The algorithm exploits an intrinsic property of a...
Pierre Roy, Jean-Julien Aucouturier, Franço...