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IJCAI
1997
13 years 9 months ago
On the Role of Hierarchy for Neural Network Interpretation
In this paper, we concentrate on the expressive power of hierarchical structures in neural networks. Recently, the so-called SplitNet model was introduced. It develops a dynamic n...
Jürgen Rahmel, Christian Blum, Peter Hahn
IPCV
2008
13 years 9 months ago
Robust Hough-Based Symbol Recognition Using Knowledge-Based Hierarchical Neural Networks
Abstract - A robust method for symbol recognition is presented that utilizes a compact signature based on a modified Hough Transform (HT) and knowledge-based hierarchical neural ne...
Alexander Wong, William Bishop
NETWORKS
2010
13 years 6 months ago
A mean-variance model for the minimum cost flow problem with stochastic arc costs
This paper considers a minimum cost flow problem where arc costs are uncertain, and the decision maker wishes to minimize both the expected flow cost and the variance of this co...
Stephen D. Boyles, S. Travis Waller
CIMCA
2005
IEEE
14 years 1 months ago
OntoBayes: An Ontology-Driven Uncertainty Model
— This paper describes an ontology-driven model, which integrates Bayesian Networks (BN) into the Ontology Web Language (OWL) to preserve the advantages of both. This model makes...
Yi Yang, Jacques Calmet
BMCBI
2011
12 years 11 months ago
A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genome-w
Background: Discovering the genetic basis of common genetic diseases in the human genome represents a public health issue. However, the dimensionality of the genetic data (up to 1...
Raphael Mourad, Christine Sinoquet, Philippe Leray