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» Hierarchical Structuring of Data on Manifolds
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AAAI
2007
13 years 10 months ago
Manifold Denoising as Preprocessing for Finding Natural Representations of Data
A natural representation of data is given by the parameters which generated the data. If the space of parameters is continuous, then we can regard it as a manifold. In practice, w...
Matthias Hein, Markus Maier
KDD
2002
ACM
193views Data Mining» more  KDD 2002»
14 years 8 months ago
Query, analysis, and visualization of hierarchically structured data using Polaris
In the last several years, large OLAP databases have become common in a variety of applications such as corporate data warehouses and scientific computing. To support interactive ...
Chris Stolte, Diane Tang, Pat Hanrahan
ICPR
2008
IEEE
14 years 2 months ago
Semi-supervised discriminant analysis based on UDP regularization
We propose a semi-supervised learning algorithm for discriminant analysis, which uses the geometric structure of both labeled and unlabeled samples and perform a manifold regulari...
Huining Qiu, Jian-Huang Lai, Jian Huang, Yu Chen
MICCAI
2010
Springer
13 years 6 months ago
Manifold Learning for Biomarker Discovery in MR Imaging
We propose a framework for the extraction of biomarkers from low-dimensional manifolds representing inter- and intra-subject brain variation in MR image data. The coordinates of ea...
Robin Wolz, Paul Aljabar, Joseph V. Hajnal, Daniel...
PAMI
2006
127views more  PAMI 2006»
13 years 7 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