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» First-order probabilistic inference
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102
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ICDM
2007
IEEE
289views Data Mining» more  ICDM 2007»
15 years 7 months ago
Latent Dirichlet Conditional Naive-Bayes Models
In spite of the popularity of probabilistic mixture models for latent structure discovery from data, mixture models do not have a natural mechanism for handling sparsity, where ea...
Arindam Banerjee, Hanhuai Shan
124
Voted
ROMAN
2007
IEEE
179views Robotics» more  ROMAN 2007»
15 years 6 months ago
A Bayesian Network Framework for Vision Based Semantic Scene Understanding
— For a robot to understand a scene, we have to infer and extract meaningful information from vision sensor data. Since scene understanding consists in recognizing several visual...
Seung-Bin Im, Keum-Sung Hwang, Sung-Bae Clio
ADC
2006
Springer
188views Database» more  ADC 2006»
15 years 6 months ago
Discovering task-oriented usage pattern for web recommendation
Web transaction data usually convey user task-oriented behaviour pattern. Web usage mining technique is able to capture such informative knowledge about user task pattern from usa...
Guandong Xu, Yanchun Zhang, Xiaofang Zhou
WACV
2005
IEEE
15 years 6 months ago
Multi-View Face Tracking with Factorial and Switching HMM
Dynamic face pose change and noise make it difficult to track multi-view faces in a cluttering environment. In this paper, we propose a graphical model based method, which combin...
Peng Wang, Qiang Ji
NN
1997
Springer
174views Neural Networks» more  NN 1997»
15 years 4 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani