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» The Kernel Trick for Distances
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PR
2007
88views more  PR 2007»
13 years 7 months ago
Robust kernel Isomap
Isomap is one of widely-used low-dimensional embedding methods, where geodesic distances on a weighted graph are incorporated with the classical scaling (metric multidimensional s...
Heeyoul Choi, Seungjin Choi
SSPR
2010
Springer
13 years 6 months ago
An Empirical Comparison of Kernel-Based and Dissimilarity-Based Feature Spaces
The aim of this paper is to find an answer to the question: What is the difference between dissimilarity-based classifications(DBCs) and other kernelbased classifications(KBCs)?...
Sang-Woon Kim, Robert P. W. Duin
GMP
2006
IEEE
120views Solid Modeling» more  GMP 2006»
14 years 1 months ago
Spectral Sequencing Based on Graph Distance
The construction of linear mesh layouts has found various applications, such as implicit mesh filtering and mesh streaming, where a variety of layout quality criteria, e.g., span ...
Rong Liu, Hao Zhang 0002, Oliver van Kaick
RIAO
2000
13 years 9 months ago
Classification of Radiographs in the 'Image Retrieval in Medical Applications' - System
In this paper we present a new approach to classifying radiographs, which is the first important task of the IRMA system. Given an image, we compute posterior probabilities for ea...
Jörg Dahmen, Thomas Theiner, Daniel Keysers, ...
EGC
2009
Springer
13 years 5 months ago
Discrepancy Analysis of Complex Objects Using Dissimilarities
Abstract. In this article we consider objects for which we have a matrix of dissimilarities and we are interested in their links with covariates. We focus on state sequences for wh...
Matthias Studer, Gilbert Ritschard, Alexis Gabadin...