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SADM
2010
196views more  SADM 2010»
13 years 2 months ago
Bayesian adaptive nearest neighbor
: The k nearest neighbor classification (k-NN) is a very simple and popular method for classification. However, it suffers from a major drawback, it assumes constant local class po...
Ruixin Guo, Sounak Chakraborty
CVPR
2006
IEEE
14 years 9 months ago
SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition
We consider visual category recognition in the framework of measuring similarities, or equivalently perceptual distances, to prototype examples of categories. This approach is qui...
Alexander C. Berg, Hao Zhang 0003, Jitendra Malik,...
ECCV
2010
Springer
14 years 29 days ago
Fast Approximate Nearest Neighbor Methods for Non-Euclidean Manifolds with Applications to Human Activity Analysis in Videos
Approximate Nearest Neighbor (ANN) methods such as Locality Sensitive Hashing, Semantic Hashing, and Spectral Hashing, provide computationally ecient procedures for nding objects...
Rizwan Chaudhry, Yuri Ivanov
FOCS
2004
IEEE
13 years 11 months ago
An Optimal Randomised Cell Probe Lower Bound for Approximate Nearest Neighbour Searching
We consider the approximate nearest neighbour search problem on the Hamming cube {0, 1}d. We show that a randomised cell probe algorithm that uses polynomial storage and word size...
Amit Chakrabarti, Oded Regev
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
13 years 9 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar