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» Using Random Forests in the Structured Language Model
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ICML
2004
IEEE
14 years 9 months ago
Kernel conditional random fields: representation and clique selection
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
John D. Lafferty, Xiaojin Zhu, Yan Liu
VC
2002
129views more  VC 2002»
13 years 8 months ago
Modeling a Murex cabritii sea shell with a structured implicit surface modeler
Implicit surface modeling systems have been used since the mid-1980s for the generation of cartoon-like characters. Recently implicit models combined with constructive solid geome...
Callum Galbraith, Przemyslaw Prusinkiewicz, Brian ...
CVPR
2009
IEEE
15 years 3 months ago
Max-Margin Hidden Conditional Random Fields for Human Action Recognition
We present a new method for classification with structured latent variables. Our model is formulated using the max-margin formalism in the discriminative learning literature. We...
Yang Wang 0003, Greg Mori
ICSE
2005
IEEE-ACM
14 years 8 months ago
Data structure repair using goal-directed reasoning
Data structure repair is a promising technique for enabling programs to execute successfully in the presence of otherwise fatal data structure corruption errors. Previous research...
Brian Demsky, Martin C. Rinard
CVPR
2010
IEEE
14 years 2 months ago
Neuron Geometry Extraction by Perceptual Grouping in ssTEM images
In the field of neuroanatomy, automatic segmentation of electron microscopy images is becoming one of the main limiting factors in getting new insights into the functional struct...
Verena Kaynig, Thomas Fuchs, Joachim Buhmann