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» Inferring Hidden Causal Structure
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CDC
2008
IEEE
14 years 5 months ago
Shannon meets Bellman: Feature based Markovian models for detection and optimization
— The goal of this paper is to develop modeling techniques for complex systems for the purposes of control, estimation, and inference: (i) A new class of Hidden Markov Models is ...
Sean P. Meyn, George Mathew
BMCBI
2010
147views more  BMCBI 2010»
13 years 11 months ago
Learning biological network using mutual information and conditional independence
Background: Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a revers...
Dong-Chul Kim, Xiaoyu Wang, Chin-Rang Yang, Jean G...
BMCBI
2010
106views more  BMCBI 2010»
13 years 11 months ago
A novel approach for haplotype-based association analysis using family data
Background: Haplotype-based approaches have been extensively studied for case-control association mapping in recent years. It has been shown that haplotype methods can provide mor...
Yixuan Chen, Xin Li, Jing Li
FCSC
2010
238views more  FCSC 2010»
13 years 8 months ago
Knowledge discovery through directed probabilistic topic models: a survey
Graphical models have become the basic framework for topic based probabilistic modeling. Especially models with latent variables have proved to be effective in capturing hidden str...
Ali Daud, Juanzi Li, Lizhu Zhou, Faqir Muhammad
CVPR
2004
IEEE
15 years 28 days ago
A Unified Spatio-Temporal Articulated Model for Tracking
Tracking articulated objects in image sequences remains a challenging problem, particularly in terms of the ability to localize the individual parts of an object given selfocclusi...
Xiangyang Lan, Daniel P. Huttenlocher