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» The Dark Side of Object Learning: Learning Objects
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NIPS
2007
15 years 5 months ago
Agreement-Based Learning
The learning of probabilistic models with many hidden variables and nondecomposable dependencies is an important and challenging problem. In contrast to traditional approaches bas...
Percy Liang, Dan Klein, Michael I. Jordan
VISAPP
2008
15 years 5 months ago
Continuous Learning of Simple Visual Concepts Using Incremental Kernel Density Estimation
In this paper we propose a method for continuous learning of simple visual concepts. The method continuously associates words describing observed scenes with automatically extracte...
Danijel Skocaj, Matej Kristan, Ales Leonardis
ESANN
2001
15 years 5 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
PR
2006
93views more  PR 2006»
15 years 4 months ago
Learning the kernel parameters in kernel minimum distance classifier
Choosing appropriate values for kernel parameters is one of the key problems in many kernel-based methods because the values of these parameters have significant impact on the per...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou
CVPR
2003
IEEE
16 years 6 months ago
Learning a discriminative classifier using shape context distances
For purpose of object recognition, we learn one discriminative classifier based on one prototype, using shape context distances as the feature vector. From multiple prototypes, th...
Hao Zhang 0003, Jitendra Malik