This paper presents an extensive evaluation, on artificial datasets, of EDY, an unsupervised algorithm for automatically synthesizing a Structured Hidden Markov Model (S-HMM) from ...
Wepropose in this paper a modularlearning environmentfor proteinmodeling.In this system,the protein modelingproblemis tackledin twosuccessive phases. First, partial structural inf...
The compositional nature of visual objects significantly limits their representation complexity and renders learning of structured object models tractable. Adopting this modeling ...
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
The aim of this paper is to describe and evaluate a system that automates a part of the transition from analytical to tectogrammatical tree structures within the Prague Dependency...