Structured prediction tasks pose a fundamental trade-off between the need for model complexity to increase predictive power and the limited computational resources for inference i...
We introduce a novel framework for simultaneous structure and parameter learning in hidden-variable conditional probability models, based on an entropic prior and a solution for i...
Despite its state-of-the-art performance, the Data Oriented Parsing (DOP) model has been shown to suffer from biased parameter estimation, and the good performance seems more the ...
Semantic Web Services facilitate activities including automatic discovery and composition of Web Services. Research initiatives such as WSMO have been developing specifications fo...
A radius–based separation of selection and recombination spheres in diffusion model EAs is introduced, enabling a new taxonomy, oriented towards information flow analysis. It a...