Dependency parsers show syntactic relations between words using a directed graph, but comparing dependency parsers is difficult because of differences in theoretical models. We de...
The models used for analyzing functional MRI (fMRI) data have profound impact on the detection of active brain areas. In this paper temporal and spatial linear subspace models for...
Abstract. Topic models are a discrete analogue to principle component analysis and independent component analysis that model topic at the word level within a document. They have ma...
A Gaussian mixture model (GMM) estimates a probability density function using the expectation-maximization algorithm. However, it may lead to a poor performance or inconsistency. T...
A non-dominated sorting genetic algorithm is used to evolve models of learning from different theories for multiple tasks. Correlation analysis is performed to identify parameters...