In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the dependency structure than directed graphical mode...
Sushmita Roy, Terran Lane, Margaret Werner-Washbur...
Practical data mining rarely falls exactly into the supervised learning scenario. Rather, the growing amount of unlabeled data poses a big challenge to large-scale semi-supervised...
In this paper we show that many kernel methods can be adapted to deal with indefinite kernels, that is, kernels which are not positive semidefinite. They do not satisfy Mercer...
ing from Robot Sensor Data using Hidden Markov Models Laura Firoiu, Paul Cohen Computer Science Department, LGRC University of Massachusetts at Amherst, Box 34610 Amherst, MA 01003...
E cient learning of DFA is a challenging research problem in grammatical inference. Both exact and approximate (in the PAC sense) identi ability of DFA from examples is known to b...