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» Unsupervised Nonlinear Manifold Learning
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DSP
2007
13 years 9 months ago
Blind separation of nonlinear mixtures by variational Bayesian learning
Blind separation of sources from nonlinear mixtures is a challenging and often ill-posed problem. We present three methods for solving this problem: an improved nonlinear factor a...
Antti Honkela, Harri Valpola, Alexander Ilin, Juha...
NIPS
2003
13 years 10 months ago
Non-linear CCA and PCA by Alignment of Local Models
We propose a non-linear Canonical Correlation Analysis (CCA) method which works by coordinating or aligning mixtures of linear models. In the same way that CCA extends the idea of...
Jakob J. Verbeek, Sam T. Roweis, Nikos A. Vlassis
CVPR
2005
IEEE
14 years 11 months ago
Face Recognition with Image Sets Using Manifold Density Divergence
In many automatic face recognition applications, a set of a person's face images is available rather than a single image. In this paper, we describe a novel method for face r...
Ognjen Arandjelovic, Gregory Shakhnarovich, John F...
CVPR
2008
IEEE
14 years 11 months ago
Clustering and dimensionality reduction on Riemannian manifolds
We propose a novel algorithm for clustering data sampled from multiple submanifolds of a Riemannian manifold. First, we learn a representation of the data using generalizations of...
Alvina Goh, René Vidal
ICDM
2006
IEEE
225views Data Mining» more  ICDM 2006»
14 years 3 months ago
Adaptive Kernel Principal Component Analysis with Unsupervised Learning of Kernels
Choosing an appropriate kernel is one of the key problems in kernel-based methods. Most existing kernel selection methods require that the class labels of the training examples ar...
Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen