219 search results - page 12 / 44 » Learning the Dimensionality of Hidden Variables |
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ICML
2010
IEEE
14 years 10 months ago
2010
IEEE
A sparse representation of Support Vector Machines (SVMs) with respect to input features is desirable for many applications. In this paper, by introducing a 0-1 control variable t...
PAMI
2008
14 years 9 months ago
2008
Abstract-- Extending traditional models for discriminative labeling of structured data to include higher-order structure in the labels results in an undesirable exponential increas...
ECML
2007
Springer
15 years 3 months ago
2007
Springer
Abstract. Clustering has recently enjoyed progress via spectral methods which group data using only pairwise affinities and avoid parametric assumptions. While spectral clustering ...
ICTAI
2005
IEEE
15 years 3 months ago
2005
IEEE
In this paper, we propose a novel stochastic framework for unsupervised manifold learning. The latent variables are introduced, and the latent processes are assumed to characteriz...
93
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ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
In dimensionality reduction approaches, the data are typically embedded in a Euclidean latent space. However for some data sets this is inappropriate. For example, in human motion...