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PAMI
2006
178views more  PAMI 2006»
15 years 6 months ago
Learning Nonlinear Image Manifolds by Global Alignment of Local Linear Models
Appearance-based methods, based on statistical models of the pixel values in an image (region) rather than geometrical object models, are increasingly popular in computer vision. I...
Jakob J. Verbeek
CVIU
2011
14 years 10 months ago
Graph attribute embedding via Riemannian submersion learning
In this paper, we tackle the problem of embedding a set of relational structures into a metric space for purposes of matching and categorisation. To this end, we view the problem ...
Haifeng Zhao, Antonio Robles-Kelly, Jun Zhou, Jian...
ESANN
2001
15 years 8 months ago
A divide-and-conquer learning architecture for predicting unknown motion
Time varying environments or model selection problems lead to crucial dilemmas in identification and control science. In this paper, we propose a modular prediction scheme consisti...
Patrice Wira, Jean-Philippe Urban, Julien Gresser
FLAIRS
2006
15 years 8 months ago
Full Restart Speeds Learning
Because many real-world problems can be represented and solved as constraint satisfaction problems, the development of effective, efficient constraint solvers is important. A solv...
Smiljana Petrovic, Susan L. Epstein
ECSQARU
2009
Springer
16 years 1 months ago
Maximum Likelihood Learning of Conditional MTE Distributions
We describe a procedure for inducing conditional densities within the mixtures of truncated exponentials (MTE) framework. We analyse possible conditional MTE specifications and pr...
Helge Langseth, Thomas D. Nielsen, Rafael Rum&iacu...