Linear dimensionality reduction (LDR) is quite important in pattern recognition due to its efficiency and low computational complexity. In this paper, we extend the two-class Chern...
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
Dependency-based representations of natural language syntax require a fine balance between structural flexibility and computational complexity. In previous work, several constra...
In recent years tree kernels have been proposed for the automatic learning of natural language applications. Unfortunately, they show (a) an inherent super linear complexity and (...
BUILD-IT is a planning tool based on computer vision technology, supporting complex planning and composition tasks. A group of people, seated around a table, interact with objects...