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» Bayesian Inference for Sparse Generalized Linear Models
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124
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ICDM
2008
IEEE
184views Data Mining» more  ICDM 2008»
15 years 8 months ago
Bayesian Co-clustering
In recent years, co-clustering has emerged as a powerful data mining tool that can analyze dyadic data connecting two entities. However, almost all existing co-clustering techniqu...
Hanhuai Shan, Arindam Banerjee
145
Voted
HUMO
2007
Springer
15 years 8 months ago
Multi-activity Tracking in LLE Body Pose Space
We present a method to simultaneously estimate 3d body pose and action categories from monocular video sequences. Our approach learns a lowdimensional embedding of the pose manifol...
Tobias Jaeggli, Esther Koller-Meier, Luc J. Van Go...
127
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CVPR
1999
IEEE
16 years 3 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
15 years 8 months ago
A Bayesian approach to empirical local linearization for robotics
— Local linearizations are ubiquitous in the control of robotic systems. Analytical methods, if available, can be used to obtain the linearization, but in complex robotics system...
Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, St...
114
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BMCBI
2010
142views more  BMCBI 2010»
15 years 1 months ago
pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree
Background: Likelihood-based phylogenetic inference is generally considered to be the most reliable classification method for unknown sequences. However, traditional likelihood-ba...
Frederick A. Matsen III, Robin B. Kodner, E. Virgi...