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222
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ICANN
2010
Springer
15 years 8 months ago
2010
Springer
Abstract. Learning algorithms relying on Gibbs sampling based stochastic approximations of the log-likelihood gradient have become a common way to train Restricted Boltzmann Machin...
198
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CVPR
2003
IEEE
16 years 9 months ago
2003
IEEE
In this paper, a novel method to learn the intrinsic object structure for robust visual tracking is proposed. The basic assumption is that the parameterized object state lies on a...
227
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ICCV
2005
IEEE
16 years 8 months ago
2005
IEEE
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
160
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ICML
2007
IEEE
16 years 7 months ago
2007
IEEE
In many applications it is desirable to learn from several kernels. "Multiple kernel learning" (MKL) allows the practitioner to optimize over linear combinations of kern...
158
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ECCV
2010
Springer
16 years 2 days ago
2010
Springer
Recent progress in per-pixel object class labeling of natural images can be attributed to the use of multiple types of image features and sound statistical learning approaches. Wit...