Abstract. K-anonymisation is an approach to protecting private information contained within a dataset. Many k-anonymisation methods have been proposed recently and one class of suc...
Abstract. In recent years a bundle of parallel and distributed algorithms for verification of finite state systems has appeared. We survey distributed-memory enumerative LTL mode...
We derive the clustering problem from first principles showing that the goal of achieving a probabilistic, or ”hard”, multi class clustering result is equivalent to the algeb...
We present the first unsupervised approach to the problem of learning a semantic parser, using Markov logic. Our USP system transforms dependency trees into quasi-logical forms, r...
We investigate how random projection can best be used for clustering high dimensional data. Random projection has been shown to have promising theoretical properties. In practice,...