This paper presents and compares results for three types of connectionist networks on perceptual learning tasks: [A] Multi-layered converging networks of neuron-like units, with e...
In this paper we describe Racer, which can be considered as a core inference engine for the semantic web. The Racer inference server offers two APIs that are already used by at le...
We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...
Lustre is a formal synchronous declarative language widely used for modeling and specifying safety-critical applications in the elds of avionics, transportation or energy productio...
Virginia Papailiopoulou, Laya Madani, Lydie du Bou...
This work explores issues of computational disclosure control. We examine assumptions in the foundations of traditional problem statements and abstract models. We offer a comprehe...
Rick Crawford, Matt Bishop, Bhume Bhumiratana, Lis...