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ICML
1994
IEEE
15 years 1 months ago
Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms
With the goal of reducing computational costs without sacrificing accuracy, we describe two algorithms to find sets of prototypes for nearest neighbor classification. Here, the te...
David B. Skalak
STOC
2006
ACM
244views Algorithms» more  STOC 2006»
15 years 9 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
109
Voted
TIP
2002
116views more  TIP 2002»
14 years 9 months ago
Adaptive approximate nearest neighbor search for fractal image compression
Fractal image encoding is a computationally intensive method of compression due to its need to find the best match between image sub-blocks by repeatedly searching a large virtual...
Chong Sze Tong, Man Wong
ACIVS
2006
Springer
15 years 3 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...