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ICDM
2002
IEEE
158views Data Mining» more  ICDM 2002»
15 years 4 months ago
Adaptive dimension reduction for clustering high dimensional data
It is well-known that for high dimensional data clustering, standard algorithms such as EM and the K-means are often trapped in local minimum. Many initialization methods were pro...
Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha, Horst...
ICB
2007
Springer
238views Biometrics» more  ICB 2007»
15 years 3 months ago
Keypoint Identification and Feature-Based 3D Face Recognition
We present a feature-based 3D face recognition algorithm and propose a keypoint identification technique which is repeatable and identifies keypoints where shape variation is high ...
Ajmal S. Mian, Mohammed Bennamoun, Robyn A. Owens
ESANN
2007
15 years 1 months ago
Estimation of tangent planes for neighborhood graph correction
Local algorithms for non-linear dimensionality reduction [1], [2], [3], [4], [5] and semi-supervised learning algorithms [6], [7] use spectral decomposition based on a nearest neig...
Karina Zapien Arreola, Gilles Gasso, Stépha...
MOR
2008
110views more  MOR 2008»
14 years 11 months ago
Alternating Projections on Manifolds
We prove that if two smooth manifolds intersect transversally, then the method of alternating projections converges locally at a linear rate. We bound the speed of convergence in ...
Adrian S. Lewis, Jérôme Malick
TNN
1998
76views more  TNN 1998»
14 years 11 months ago
Multiobjective genetic algorithm partitioning for hierarchical learning of high-dimensional pattern spaces: a learning-follows-d
— In this paper, we present a novel approach to partitioning pattern spaces using a multiobjective genetic algorithm for identifying (near-)optimal subspaces for hierarchical lea...
Rajeev Kumar, Peter Rockett