264 search results - page 5 / 53 » Factorial Learning and the EM Algorithm |
BMEI
2009
IEEE
13 years 8 months ago
2009
IEEE
The Gaussian mixture model is a powerful statistical tool in data modeling and analysis. Generally, the EM algorithm is utilized to learn the parameters of the Gaussian mixture. Ho...
CORR
2011
Springer
13 years 2 months ago
2011
Springer
There have been several recent advancements in Machine Learning community on the Entity Matching (EM) problem. However, their lack of scalability has prevented them from being app...
NIPS
1998
13 years 9 months ago
1998
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
UAI
2003
13 years 9 months ago
2003
Learning with hidden variables is a central challenge in probabilistic graphical models that has important implications for many real-life problems. The classical approach is usin...
ICPR
2004
IEEE
14 years 8 months ago
2004
IEEE
How to determine the number of clusters is an intractable problem in clustering analysis. In this paper, we propose a new learning paradigm named Maximum Weighted Likelihood (MwL)...