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ML
2010
ACM
151views Machine Learning» more  ML 2010»
14 years 8 months ago
Inductive transfer for learning Bayesian networks
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
BMCBI
2007
127views more  BMCBI 2007»
14 years 9 months ago
A Latent Variable Approach for Meta-Analysis of Gene Expression Data from Multiple Microarray Experiments
Background: With the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across...
Hyungwon Choi, Ronglai Shen, Arul M. Chinnaiyan, D...
JSAI
2005
Springer
15 years 3 months ago
Learning Stochastic Logical Automaton
Abstract. This paper is concerned with algorithms for the logical generalisation of probabilistic temporal models from examples. The algorithms combine logic and probabilistic mode...
Hiroaki Watanabe, Stephen Muggleton
SIGGRAPH
1995
ACM
15 years 1 months ago
Time-dependent three-dimensional intravascular ultrasound
Intravascular ultrasonography and x-ray angiography provide two complimentary techniques for imaging the moving coronary arteries. We present a technique that combines the strengt...
Jed Lengyel, Donald P. Greenberg, Richard Popp
CVPR
2007
IEEE
15 years 11 months ago
3D Probabilistic Feature Point Model for Object Detection and Recognition
This paper presents a novel statistical shape model that can be used to detect and localise feature points of a class of objects in images. The shape model is inspired from the 3D...
Sami Romdhani, Thomas Vetter