We generalise the Gaussian process (GP) framework for regression by learning a nonlinear transformation of the GP outputs. This allows for non-Gaussian processes and non-Gaussian ...
Edward Snelson, Carl Edward Rasmussen, Zoubin Ghah...
A natural language generation system must generate expressions that allow a reader to identify the entities to which they refer. This paper describes the creation of referring-exp...
Jill Nickerson, Stuart M. Shieber, Barbara J. Gros...
Record linkage identifies multiple records referring to the same entity even if they are not bit-wise identical. It is thus an essential technology for data integration and data c...
Complex model editing activities are frequently performed to realize various model evolution tasks (e.g., model scalability, weaving aspects into models, and model refactoring). In...
Yu Sun, Jeff Gray, Christoph Wienands, Michael Gol...
Mixture of Gaussians (MoG) model is a useful tool in statistical learning. In many learning processes that are based on mixture models, computational requirements are very demandin...
Jacob Goldberger, Hayit Greenspan, Jeremie Dreyfus...