PAMI
2011
13 years 7 months ago
2011
— This paper introduces a product quantization based approach for approximate nearest neighbor search. The idea is to decomposes the space into a Cartesian product of low dimensi...
IJDAR
2010
13 years 9 months ago
2010
We study online classification of isolated handwritten symbols using distance measures on spaces of curves. We compare three distance-based measures on a vector space representatio...
VLSISP
2010
13 years 11 months ago
2010
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
PVLDB
2008
14 years 1 days ago
2008
Uncertainty pervades many domains in our lives. Current real-life applications, e.g., location tracking using GPS devices or cell phones, multimedia feature extraction, and sensor...
JPDC
2007
14 years 13 days ago
2007
High-dimensional problems arising from robot motion planning, biology, data mining, and geographic information systems often require the computation of k nearest neighbor (knn) gr...
TALG
2008
14 years 14 days ago
2008
We present simple, fully dynamic and kinetic data structures, which are variants of a dynamic two-dimensional range tree, for maintaining the closest pair and all nearest neighbors...
BMCBI
2006
14 years 18 days ago
2006
Background: Various statistical and machine learning methods have been successfully applied to the classification of DNA microarray data. Simple instance-based classifiers such as...
ICASSP
2010
IEEE
14 years 22 days ago
2010
IEEE
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...
ICASSP
2010
IEEE
14 years 22 days ago
2010
IEEE
We propose an algorithm for detecting bridges and estimating geodesic distances from a set of noisy samples of an underlying manifold. Finding geodesics on a nearest neighbors gra...
SODA
1993
ACM
14 years 1 months ago
1993
ACM
We introduce a new method for nding several types of optimal k-point sets, minimizing perimeter, diameter, circumradius, and related measures, by testing sets of the O(k) nearest ...