146 search results - page 10 / 30 » Learning with Neural Networks in the Domain of Graphs |
GECCO
2010
Springer
15 years 27 days ago
2010
Springer
Multiobjective evolutionary algorithms have long been applied to engineering problems. Lately they have also been used to evolve behaviors for intelligent agents. In such applicat...
IJCNN
2006
IEEE
15 years 3 months ago
2006
IEEE
— Over time, neural networks have proven to be extremely powerful tools for data exploration with the capability to discover previously unknown dependencies and relationships in ...
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the dependency structure than directed graphical mode...
ICANN
2007
Springer
15 years 3 months ago
2007
Springer
Abstract. Classification of structured data (i.e., data that are represented as graphs) is a topic of interest in the machine learning community. This paper presents a different,...
CSB
2005
IEEE
15 years 3 months ago
2005
IEEE
Artificial Neural Networks (ANN) were employed to predict daylily (Hemerocalli spp.) hybrids from known characteristics of parents used in hybridization. Features such as height, ...