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IDA
2003
Springer
15 years 11 months ago
Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing Dependencies
Abstract. Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any mode...
Allan Tucker, Xiaohui Liu
PKDD
2009
Springer
146views Data Mining» more  PKDD 2009»
15 years 11 months ago
Parallel Subspace Sampling for Particle Filtering in Dynamic Bayesian Networks
Monitoring the variables of real world dynamic systems is a difficult task due to their inherent complexity and uncertainty. Particle Filters (PF) perform that task, yielding prob...
Eva Besada-Portas, Sergey M. Plis, Jesús Ma...
AAAI
2008
15 years 8 months ago
A General Framework for Generating Multivariate Explanations in Bayesian Networks
Many existing explanation methods in Bayesian networks, such as Maximum a Posteriori (MAP) assignment and Most Probable Explanation (MPE), generate complete assignments for target...
Changhe Yuan, Tsai-Ching Lu
AAAI
2008
15 years 8 months ago
Reducing Particle Filtering Complexity for 3D Motion Capture using Dynamic Bayesian Networks
Particle filtering algorithms can be used for the monitoring of dynamic systems with continuous state variables and without any constraints on the form of the probability distribu...
Cédric Rose, Jamal Saboune, François...
LREC
2010
190views Education» more  LREC 2010»
15 years 8 months ago
Applying a Dynamic Bayesian Network Framework to Transliteration Identification
Identification of transliterations is aimed at enriching multilingual lexicons and improving performance in various Natural Language Processing (NLP) applications including Cross ...
Peter Nabende