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ECCV
2008
Springer
14 years 5 months ago
Constrained Maximum Likelihood Learning of Bayesian Networks for Facial Action Recognition
Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...
Cassio Polpo de Campos, Yan Tong, Qiang Ji
IJAR
2010
130views more  IJAR 2010»
13 years 2 months ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki
UAI
2003
13 years 5 months ago
Robust Independence Testing for Constraint-Based Learning of Causal Structure
This paper considers a method that combines ideas from Bayesian learning, Bayesian network inference, and classical hypothesis testing to produce a more reliable and robust test o...
Denver Dash, Marek J. Druzdzel
CVPR
1999
IEEE
14 years 5 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
CCS
2009
ACM
13 years 10 months ago
A framework for quantitative security analysis of machine learning
We propose a framework for quantitative security analysis of machine learning methods. Key issus of this framework are a formal specification of the deployed learning model and a...
Pavel Laskov, Marius Kloft