We experimentally evaluate bagging and six other randomization-based approaches to creating an ensemble of decision-tree classifiers. Bagging uses randomization to create multipl...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...
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...
We study the random m-ary search tree model (where m stands for the number of branches of the search tree), an important problem for data storage in computer science, using a varie...
Satya N. Majumdar, David S. Dean, Paul L. Krapivsk...
Abstract. The members of Martin-L¨of random closed sets under a distribution studied by Barmpalias et al. are exactly the infinite paths through Martin-L¨of random Galton-Watson...
We introduce a new interpretation of multiscale random fields (MSRFs) that admits efficient optimization in the framework of regular (single level) random fields (RFs). It is base...
Longin Jan Latecki, ChengEn Lu, Marc Sobel, Xiang ...