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CRV
2011
IEEE
5 months 11 days ago
2011
IEEE
— Algorithmic problem reduction is a fundamental approach to problem solving in many fields, including robotics. To solve a problem using this scheme, we must reduce the problem...
SDM
2011
SIAM
8 months 13 days ago
2011
SIAM
While the social and information networks have become ubiquitous, the challenge of collecting complete network data still persists. Many times the collected network data is incomp...
SDM
2011
SIAM
8 months 13 days ago
2011
SIAM
Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
JCPHY
2011
8 months 15 days ago
2011
A new numerical method for approximating highly oscillatory wave fields as a superposition of Gaussian beams is presented. The method estimates the number of beams and their para...
ICTAI
2010
IEEE
1 years 2 months ago
2010
IEEE
This work deals with a new technique for the estimation of the parameters and number of components in a finite mixture model. The learning procedure is performed by means of a expe...
ICIAR
2010
Springer
1 years 2 months ago
2010
Springer
Image segmentation is a critical low-level visual routine for robot perception. However, most image segmentation approaches are still too slow to allow real-time robot operation. I...
EMNLP
2010
1 years 3 months ago
2010
In this paper, we introduce a method that automatically builds text classifiers in a new language by training on already labeled data in another language. Our method transfers the...
AMDO
2010
Springer
1 years 4 months ago
2010
Springer
In this paper an approach is described to estimate 3D pose using a part based stochastic method. A proposed representation of the human body is explored defined over joints that e...
PR
2006
1 years 5 months ago
2006
Fuzzy-clustering methods, such as fuzzy k-means and Expectation Maximization, allow an object to be assigned to multiple clusters with different degrees of membership. However, th...
NIPS
1998
1 years 6 months ago
1998
We present the CEM (Conditional Expectation Maximization) algorithm as an extension of the EM (Expectation Maximization) algorithm to conditional density estimation under missing ...
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