Probability trees (or Probability Estimation Trees, PET’s) are decision trees with probability distributions in the leaves. Several alternative approaches for learning probabilit...
Daan Fierens, Jan Ramon, Hendrik Blockeel, Maurice...
Classification trees are widely used in the machine learning and data mining communities for modeling propositional data. Recent work has extended this basic paradigm to probabili...
Jennifer Neville, David Jensen, Lisa Friedland, Mi...
Randomized protocols for hiding private information can often be regarded as noisy channels in the informationtheoretic sense, and the inference of the concealed information can b...
Two basic problems in image interpretation are: a) determining which interpretations are the most plausible amoungst many possibilities; and b) controlling the search for plausibl...
There has been increasing number of independently proposed randomization methods in different stages of decision tree construction to build multiple trees. Randomized decision tre...
Wei Fan, Ed Greengrass, Joe McCloskey, Philip S. Y...