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» Bayesian Parameter Estimation: A Monte Carlo Approach
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JMLR
2010
163views more  JMLR 2010»
13 years 2 months ago
Active Sequential Learning with Tactile Feedback
We consider the problem of tactile discrimination, with the goal of estimating an underlying state parameter in a sequential setting. If the data is continuous and highdimensional...
Hannes Saal, Jo-Anne Ting, Sethu Vijayakumar
CSB
2003
IEEE
153views Bioinformatics» more  CSB 2003»
14 years 19 days ago
Combining Microarrays and Biological Knowledge for Estimating Gene Networks via Bayesian Networks
We propose a statistical method for estimating a gene network based on Bayesian networks from microarray gene expression data together with biological knowledge including protein-...
Seiya Imoto, Tomoyuki Higuchi, Takao Goto, Kousuke...
AUTOMATICA
2002
80views more  AUTOMATICA 2002»
13 years 7 months ago
Robust control of nonlinear systems with parametric uncertainty
Probabilistic robustness analysis and synthesis for nonlinear systems with uncertain parameters are presented. Monte Carlo simulation is used to estimate the likelihood of system ...
Qian Wang, Robert F. Stengel
ICMCS
2007
IEEE
191views Multimedia» more  ICMCS 2007»
14 years 1 months ago
Variable Number of "Informative" Particles for Object Tracking
Particle filter is a sequential Monte Carlo method for object tracking in a recursive Bayesian filtering framework. The efficiency and accuracy of the particle filter depends on t...
Yu Huang, Joan Llach
AUTOMATICA
2010
96views more  AUTOMATICA 2010»
13 years 7 months ago
On resampling and uncertainty estimation in Linear System Identification
Linear System Identification yields a nominal model parameter, which minimizes a specific criterion based on the single inputoutput data set. Here we investigate the utility of va...
Simone Garatti, Robert R. Bitmead