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ICANN
2007
Springer
14 years 4 months ago
A Topology-Independent Similarity Measure for High-Dimensional Feature Spaces
In the field of computer vision feature matching in high dimensional feature spaces is a commonly used technique for object recognition. One major problem is to find an adequate s...
Jochen Kerdels, Gabriele Peters
PODS
2000
ACM
120views Database» more  PODS 2000»
14 years 1 months ago
Indexing the Edges - A Simple and Yet Efficient Approach to High-Dimensional Indexing
In this paper, we propose a new tunable index scheme, called iMinMax , that maps points in high dimensional spaces to single dimension values determined by their maximum or minimu...
Beng Chin Ooi, Kian-Lee Tan, Cui Yu, Stépha...
NIPS
2003
13 years 11 months ago
Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data
In this paper we introduce a new underlying probabilistic model for principal component analysis (PCA). Our formulation interprets PCA as a particular Gaussian process prior on a ...
Neil D. Lawrence
CORR
2010
Springer
219views Education» more  CORR 2010»
13 years 10 months ago
Clustering high dimensional data using subspace and projected clustering algorithms
: Problem statement: Clustering has a number of techniques that have been developed in statistics, pattern recognition, data mining, and other fields. Subspace clustering enumerate...
Rahmat Widia Sembiring, Jasni Mohamad Zain, Abdull...
CBMS
2003
IEEE
14 years 1 months ago
Planar Arrangement of High-Dimensional Biomedical Data Sets by Isomap Coordinates
This article addresses 2-dimensional layout of high-dimensional biomedical datasets, which is useful for browsing them efficiently. We employ the Isomap technique, which is based ...
Ik Soo Lim, Pablo de Heras Ciechomski, Sofiane Sar...