Future microprocessors will be highly susceptible to transient errors as the sizes of transistors decrease due to CMOS scaling. Prior techniques advocated full scale structural or...
In this paper we present decomposable priors, a family of priors over structure and parameters of tree belief nets for which Bayesian learning with complete observations is tracta...
A recurring theme during the CODATA 2000 conference (Lake Maggiore, Italy, 15 - 19 October 2000) was the increasing convergence in data-rich branches of science between the storag...
This paper has no novel learning or statistics: it is concerned with making a wide class of preexisting statistics and learning algorithms computationally tractable when faced wit...
Inspired by “GoogleTM Sets” and Bayesian sets, we consider the problem of retrieving complex objects and relations among them, i.e., ground atoms from a logical concept, given...