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TMI
2008
66views more  TMI 2008»
13 years 8 months ago
Feature Normalization via Expectation Maximization and Unsupervised Nonparametric Classification For M-FISH Chromosome Images
Multicolor fluorescence in situ hybridization (M-FISH) techniques provide color karyotyping that allows simultaneous analysis of numerical and structural abnormalities of whole hum...
Hyohoon Choi, Alan C. Bovik, Kenneth R. Castleman
UAI
2003
13 years 10 months ago
Large-Sample Learning of Bayesian Networks is NP-Hard
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
David Maxwell Chickering, Christopher Meek, David ...
CVPR
2004
IEEE
14 years 10 months ago
Atlanta World: An Expectation Maximization Framework for Simultaneous Low-Level Edge Grouping and Camera Calibration in Complex
Edges in man-made environments, grouped according to vanishing point directions, provide single-view constraints that have been exploited before as a precursor to both scene under...
Grant Schindler, Frank Dellaert
IICAI
2003
13 years 10 months ago
The Acyclic Bayesian Net Generator
Abstract. We present the Acyclic Bayesian Net Generator, a new approach to learn the structure of a Bayesian network using genetic algorithms. Due to the encoding mechanism, acycli...
Pankaj B. Gupta, Vicki H. Allan
NIPS
2008
13 years 10 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink