613 search results - page 55 / 123 » Learning the Structure of Linear Latent Variable Models |
ECCV
2008
Springer
14 years 10 months ago
2008
Springer
Assumptions of brightness constancy and spatial smoothness underlie most optical flow estimation methods. In contrast to standard heuristic formulations, we learn a statistical mod...
AAAI
2008
13 years 11 months ago
2008
Matrix factorization algorithms are frequently used in the machine learning community to find low dimensional representations of data. We introduce a novel generative Bayesian pro...
ICANN
2001
Springer
14 years 1 months ago
2001
Springer
Humans tend to group together related properties in order to understand complex phenomena. When modeling large problems with limited representational resources, it is important to...
TNN
1998
13 years 8 months ago
1998
—Structural learning with forgetting is an established method of using Laplace regularization to generate skeletal artificial neural networks. In this paper we develop a continu...
ICASSP
2011
IEEE
13 years 18 days ago
2011
IEEE
Building models of the structure in musical signals raises the question of how to evaluate and compare different modeling approaches. One possibility is to use the model to impute...