Practical Recurrent Learning (PRL) has been proposed as a simple learning algorithm for recurrent neural networks[1][2]. This algorithm enables learning with practical order O(n2 )...
Reasoning with both probabilistic and deterministic dependencies is important for many real-world problems, and in particular for the emerging field of statistical relational lear...
based on an abstract concept of quiescence. In the following we sketch this and a related model, describe the design of our experiments, and present the results of our simulation s...
A key factor that can dramatically reduce the search space during constraint solving is the criterion under which the variable to be instantiated next is selected. For this purpos...
: The increasing ability for the sciences to sense the world around us is resulting in a growing need for data driven applications that are under the control of workflows composed ...