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ICML
2003
IEEE
14 years 6 months ago
Learning Metrics via Discriminant Kernels and Multidimensional Scaling: Toward Expected Euclidean Representation
Distance-based methods in machine learning and pattern recognition have to rely on a metric distance between points in the input space. Instead of specifying a metric a priori, we...
Zhihua Zhang
PODS
1998
ACM
152views Database» more  PODS 1998»
13 years 9 months ago
A Cost Model for Similarity Queries in Metric Spaces
We consider the problem of estimating CPU (distance computations) and I/O costs for processing range and k-nearest neighbors queries over metric spaces. Unlike the specific case ...
Paolo Ciaccia, Marco Patella, Pavel Zezula
ADC
2003
Springer
127views Database» more  ADC 2003»
13 years 10 months ago
M+-tree : A New Dynamical Multidimensional Index for Metric Spaces
In this paper, we propose a new metric index, called M+ -tree, which is a tree dynamically organized for large datasets in metric spaces. The proposed M+ -tree takes full advantag...
Xiangmin Zhou, Guoren Wang, Jeffrey Xu Yu, Ge Yu
ISVC
2005
Springer
13 years 10 months ago
Hifocon: Object and Dimensional Coherence and Correlation in Multidimensional Visualization
In any multidimensional visualization, some information has to be compromised when projecting multidimensional data to two- or three-dimensional space. We introduce the concepts of...
Soon Tee Teoh, Kwan-Liu Ma