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ML
2010
ACM
151views Machine Learning» more  ML 2010»
13 years 6 months ago
Inductive transfer for learning Bayesian networks
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
RSS
2007
159views Robotics» more  RSS 2007»
13 years 9 months ago
Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders
— In probabilistic mobile robotics, the development of measurement models plays a crucial role as it directly influences the efficiency and the robustness of the robot’s perf...
Christian Plagemann, Kristian Kersting, Patrick Pf...
IPMI
2005
Springer
14 years 8 months ago
Bayesian Population Modeling of Effective Connectivity
Abstract. A hierarchical model based on the Multivariate Autoregessive (MAR) process is proposed to jointly model neurological time-series collected from multiple subjects, and to ...
Eric R. Cosman Jr., William M. Wells III
CSDA
2007
151views more  CSDA 2007»
13 years 8 months ago
Robust semiparametric mixing for detecting differentially expressed genes in microarray experiments
An important goal of microarray studies is the detection of genes that show significant changes in observed expressions when two or more classes of biological samples such as tre...
Marco Alfò, Alessio Farcomeni, Luca Tardell...
CVPR
2004
IEEE
14 years 10 months ago
Bayesian Assembly of 3D Axially Symmetric Shapes from Fragments
We present a complete system for the purpose of automatically assembling 3D pots given 3D measurements of their fragments commonly called sherds. A Bayesian approach is formulated...
Andrew R. Willis, David B. Cooper