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» Structure learning of Bayesian networks using constraints
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ICML
2007
IEEE
16 years 18 days ago
Modeling changing dependency structure in multivariate time series
We show how to apply the efficient Bayesian changepoint detection techniques of Fearnhead in the multivariate setting. We model the joint density of vector-valued observations usi...
Xiang Xuan, Kevin P. Murphy
CORR
2010
Springer
183views Education» more  CORR 2010»
14 years 10 months ago
Discovering shared and individual latent structure in multiple time series
This paper proposes a nonparametric Bayesian method for exploratory data analysis and feature construction in continuous time series. Our method focuses on understanding shared fe...
Suchi Saria, Daphne Koller, Anna Penn

Source Code
1763views
16 years 8 months ago
dlib C++ Library
A library for developing portable applications that deal with networking, threads (message passing, futures, etc...), graphical interfaces, complex data structures, linear algebra,...
Davis E. King
IEEEARES
2006
IEEE
15 years 5 months ago
Modeling Dependable Systems using Hybrid Bayesian Networks
A hybrid Bayesian Network (BN) is one that incorporates both discrete and continuous nodes. In our extensive applications of BNs for system dependability assessment the models are...
Martin Neil, Manesh Tailor, Norman E. Fenton, Davi...
ICANNGA
2009
Springer
145views Algorithms» more  ICANNGA 2009»
15 years 6 months ago
Supporting Scalable Bayesian Networks Using Configurable Discretizer Actuators
We propose a generalized model with configurable discretizer actuators as a solution to the problem of the discretization of massive numerical datasets. Our solution is based on a ...
Isaac Olusegun Osunmakinde, Antoine B. Bagula