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JMLR
2012
11 years 10 months ago
Low rank continuous-space graphical models
Constructing tractable dependent probability distributions over structured continuous random vectors is a central problem in statistics and machine learning. It has proven diffic...
Carl Smith, Frank Wood, Liam Paninski
NIPS
2000
13 years 9 months ago
Structure Learning in Human Causal Induction
We use graphical models to explore the question of how people learn simple causal relationships from data. The two leading psychological theories can both be seen as estimating th...
Joshua B. Tenenbaum, Thomas L. Griffiths
CVPR
2010
IEEE
14 years 3 months ago
A Diffusion Approach to Seeded Image Segmentation
Seeded image segmentation is a popular type of supervised image segmentation in computer vision and image processing. Previous methods of seeded image segmentation treat the image...
Juyong Zhang, Jianmin Zheng, Jianfei Cai
ICDM
2006
IEEE
152views Data Mining» more  ICDM 2006»
14 years 1 months ago
Application of Graph-based Data Mining to Metabolic Pathways
We present a method for finding biologically meaningful patterns on metabolic pathways using the SUBDUE graph-based relational learning system. A huge amount of biological data t...
Chang Hun You, Lawrence B. Holder, Diane J. Cook
DATAMINE
2010
161views more  DATAMINE 2010»
13 years 5 months ago
Predicting labels for dyadic data
: In dyadic prediction, the input consists of a pair of items (a dyad), and the goal is to predict the value of an observation related to the dyad. Special cases of dyadic predicti...
Aditya Krishna Menon, Charles Elkan