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KDD
2008
ACM
161views Data Mining» more  KDD 2008»
15 years 10 months ago
Locality sensitive hash functions based on concomitant rank order statistics
: Locality Sensitive Hash functions are invaluable tools for approximate near neighbor problems in high dimensional spaces. In this work, we are focused on LSH schemes where the si...
Kave Eshghi, Shyamsundar Rajaram
AAAI
2007
14 years 12 months ago
A Randomized String Kernel and Its Application to RNA Interference
String kernels directly model sequence similarities without the necessity of extracting numerical features in a vector space. Since they better capture complex traits in the seque...
Shibin Qiu, Terran Lane, Ljubomir J. Buturovic
CVPR
2010
IEEE
14 years 8 months ago
Transform Coding for Fast Approximate Nearest Neighbor Search in High Dimensions
We examine the problem of large scale nearest neighbor search in high dimensional spaces and propose a new approach based on the close relationship between nearest neighbor search...
Jonathan Brandt
APGV
2005
ACM
146views Visualization» more  APGV 2005»
15 years 3 months ago
A similarity-based approach to perceptual feature validation
Which object properties matter most in human perception may well vary according to sensory modality, an important consideration for the design of multimodal interfaces. In this st...
Theresa Cooke, Florian Steinke, Christian Wallrave...
KDD
2004
ACM
113views Data Mining» more  KDD 2004»
15 years 10 months ago
Learning spatially variant dissimilarity (SVaD) measures
Clustering algorithms typically operate on a feature vector representation of the data and find clusters that are compact with respect to an assumed (dis)similarity measure betwee...
Krishna Kummamuru, Raghu Krishnapuram, Rakesh Agra...