275 search results - page 40 / 55 » A geometric view on learning Bayesian network structures |
ICML
2005
IEEE
15 years 10 months ago
2005
IEEE
Protein fold recognition is a key step towards inferring the tertiary structures from amino-acid sequences. Complex folds such as those consisting of interacting structural repeat...
92
Voted
NIPS
2008
14 years 11 months ago
2008
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
KDD
2003
ACM
15 years 10 months ago
2003
ACM
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
ICANN
2010
Springer
14 years 10 months ago
2010
Springer
It has been one of the great challenges of neuro-symbolic integration to represent recursive logic programs using neural networks of finite size. In this paper, we propose to imple...
84
Voted
ML
2008
ACM
14 years 9 months ago
2008
ACM
Abstract. Recently, there has been an increasing interest in directed probabilistic logical models and a variety of languages for describing such models has been proposed. Although...