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» Structured Learning with Approximate Inference
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126
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BMCBI
2006
239views more  BMCBI 2006»
15 years 2 months ago
Applying dynamic Bayesian networks to perturbed gene expression data
Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...
Norbert Dojer, Anna Gambin, Andrzej Mizera, Bartek...
127
Voted
BC
2010
163views more  BC 2010»
15 years 2 days ago
Action and behavior: a free-energy formulation
We have previously tried to explain perceptual inference and learning under a free-energy principle that pursues Helmholtz's agenda to understand the brain in terms of energy ...
Karl J. Friston, Jean Daunizeau, James Kilner, Ste...
159
Voted
CVPR
2009
IEEE
16 years 9 months ago
Layered Graph Matching by Composite Cluster Sampling with Collaborative and Competitive Interactions
This paper studies a framework for matching an unknown number of corresponding structures in two images (shapes), motivated by detecting objects in cluttered background and lear...
Kun Zeng, Liang Lin, Song Chun Zhu, Xiaobai Liu
116
Voted
ICDM
2007
IEEE
289views Data Mining» more  ICDM 2007»
15 years 9 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
143
Voted
JMLR
2008
159views more  JMLR 2008»
15 years 2 months ago
Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction
Existing template-independent web data extraction approaches adopt highly ineffective decoupled strategies--attempting to do data record detection and attribute labeling in two se...
Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen