57 search results - page 1 / 12 » Learning Decision Trees with log Conditional Likelihood |
IJPRAI
2010
12 years 11 months ago
2010
DIS
2009
Springer
13 years 11 months ago
2009
Springer
Multiple-instance learning (MIL) is a generalization of the supervised learning problem where each training observation is a labeled bag of unlabeled instances. Several supervised ...
COLT
2003
Springer
13 years 10 months ago
2003
Springer
We consider three natural models of random logarithmic depth decision trees over Boolean variables. We give an efficient algorithm that for each of these models learns all but an ...
ICCV
2011
IEEE
12 years 4 months ago
2011
IEEE
This paper introduces a new formulation for discrete image labeling tasks, the Decision Tree Field (DTF), that combines and generalizes random forests and conditional random fiel...
CORR
2010
Springer
13 years 5 months ago
2010
Springer
Bayes statistics and statistical physics have the common mathematical structure, where the log likelihood function corresponds to the random Hamiltonian. Recently, it was discovere...