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NN
2008
Springer
101views Neural Networks» more  NN 2008»
13 years 7 months ago
On multidimensional scaling and the embedding of self-organising maps
The self-organising map (SOM) and its variant, visualisation induced SOM (ViSOM), have been known to yield similar results to multidimensional scaling (MDS). However, the exact co...
Hujun Yin

Publication
170views
13 years 6 months ago
Covariance Regularization for Supervised Learning in High Dimensions
This paper studies the effect of covariance regularization for classific ation of high-dimensional data. This is done by fitting a mixture of Gaussians with a regularized covaria...
Daniel L. Elliott, Charles W. Anderson, Michael Ki...
CVPR
2003
IEEE
14 years 9 months ago
Kernel Principal Angles for Classification Machines with Applications to Image Sequence Interpretation
We consider the problem of learning with instances defined over a space of sets of vectors. We derive a new positive definite kernel f(A B) defined over pairs of matrices A B base...
Lior Wolf, Amnon Shashua
APPML
2007
92views more  APPML 2007»
13 years 7 months ago
Topological grammars for data approximation
A method of topological grammars is proposed for multidimensional data approximation. For data with complex topology we define a principal cubic complex of low dimension and give...
Alexander N. Gorban, Neil R. Sumner, Andrei Yu. Zi...
ICML
2008
IEEE
14 years 8 months ago
Large scale manifold transduction
We show how the regularizer of Transductive Support Vector Machines (TSVM) can be trained by stochastic gradient descent for linear models and multi-layer architectures. The resul...
Michael Karlen, Jason Weston, Ayse Erkan, Ronan Co...