A general model is proposed for studying ranking problems. We investigate learning methods based on empirical minimization of the natural estimates of the ranking risk. The empiric...
We introduce the hash history mechanism for capturing dependencies among distributed replicas. Hash histories, consisting of a directed graph of version hashes, are independent of...
In earlier work we predicted program size would grow in the limit at a quadratic rate and up to fty generations we measured bloat O(generations1:2;1:5). On two simple benchmarks w...
We consider the global optimization problem for d-variate Lipschitz functions which, in a certain sense, do not increase too slowly in a neighborhood of the global minimizer(s). O...
Wepropose a schemefor producingLatin hypercube samples that can enhanceany of the existing sampling algorithms in Bayesiannetworks. Wetest this scheme in combinationwith the likel...