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PRL
2006
129views more  PRL 2006»
14 years 9 months ago
Learning spatial relations in object recognition
This paper studies two types of spatial relationships that can be learned from training examples for object recognition. The first one employs deformable relationships between obj...
Thang V. Pham, Arnold W. M. Smeulders
CIDM
2009
IEEE
15 years 4 months ago
A new hybrid method for Bayesian network learning With dependency constraints
Abstract— A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Baye...
Oliver Schulte, Gustavo Frigo, Russell Greiner, We...
ICASSP
2007
IEEE
15 years 4 months ago
Genomic Network Tomography
This paper considers the problem of learning cellular signaling networks from incomplete measurements of pathway activity. Cells respond to environmental changes (e.g., starvation...
Michael G. Rabbat, Mário A. T. Figueiredo, ...
ICRA
2008
IEEE
208views Robotics» more  ICRA 2008»
15 years 4 months ago
Unsupervised body scheme learning through self-perception
— In this paper, we present an approach allowing a robot to learn a generative model of its own physical body from scratch using self-perception with a single monocular camera. O...
Jürgen Sturm, Christian Plagemann, Wolfram Bu...
RECOMB
2000
Springer
15 years 1 months ago
Using Bayesian networks to analyze expression data
DNA hybridization arrays simultaneously measure the expression level for thousands of genes. These measurements provide a "snapshot" of transcription levels within the c...
Nir Friedman, Michal Linial, Iftach Nachman, Dana ...