Spatial relations are the basis for many selections users perform when they query geographic information systems (GISs). Although such query languages use natural-language-like te...
A. Rashid B. M. Shariff, Max J. Egenhofer, David M...
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Most local convergence analyses of the sequential quadratic programming (SQP) algorithm for nonlinear programming make strong assumptions about the solution, namely, that the activ...
We describe a new family of topic-ranking algorithms for multi-labeled documents. The motivation for the algorithms stems from recent advances in online learning algorithms. The a...
Abstract State Machines (ASMs) provide a sound mathematical basis for the specification and verification of systems. An application of the ASM methodology to the verification of a ...