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» The intrinsic dimensionality of graphs
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PAMI
2006
127views more  PAMI 2006»
13 years 9 months ago
Incremental Nonlinear Dimensionality Reduction by Manifold Learning
Understanding the structure of multidimensional patterns, especially in unsupervised case, is of fundamental importance in data mining, pattern recognition and machine learning. Se...
Martin H. C. Law, Anil K. Jain
JAPLL
2006
114views more  JAPLL 2006»
13 years 9 months ago
The monadic second-order logic of graphs XV: On a conjecture by D. Seese
A conjecture by D. Seese states that if a set of graphs has a decidable monadic second-order theory, then it is the image of a set of trees under a transformation defined by monad...
Bruno Courcelle
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...
STACS
1995
Springer
14 years 1 months ago
The Number of Views of Piecewise-Smooth Algebraic Objects
Abstract. A solid object in 3-dimensional space may be described by a collection of all its topologically distinct 2-dimensional appearances, its aspect graph. In this paper, we st...
Sylvain Petitjean
SPEECH
1998
118views more  SPEECH 1998»
13 years 9 months ago
Dimensionality reduction of electropalatographic data using latent variable models
We consider the problem of obtaining a reduced dimension representation of electropalatographic (EPG) data. An unsupervised learning approach based on latent variable modelling is...
Miguel Á. Carreira-Perpiñán, ...