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NN
2006
Springer
15 years 6 months ago
Machine learning in sedimentation modelling
The paper presents machine learning (ML) models that predict sedimentation in the harbour basin of the Port of Rotterdam. The important factors affecting the sedimentation process...
Biswanath Bhattacharya, Dimitri P. Solomatine
ICANN
2009
Springer
15 years 4 months ago
MINLIP: Efficient Learning of Transformation Models
Abstract. This paper studies a risk minimization approach to estimate a transformation model from noisy observations. It is argued that transformation models are a natural candidat...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
IJCNN
2006
IEEE
16 years 7 days ago
C2FS: An Algorithm for Feature Selection in Cascade Neural Networks
Wrapper-based feature selection is attractive because wrapper methods are able to optimize the features they select to the specific learning algorithm. Unfortunately, wrapper met...
Lars Backstrom, Rich Caruana
KI
2007
Springer
16 years 10 days ago
A General Framework for Encoding and Evolving Neural Networks
Abstract. In this paper we present a novel general framework for encoding and evolving networks called Common Genetic Encoding (CGE) that can be applied to both direct and indirect...
Yohannes Kassahun, Jan Hendrik Metzen, Jose de Gea...
IWANN
2005
Springer
15 years 11 months ago
Characterizing Self-developing Biological Neural Networks: A First Step Towards Their Application to Computing Systems
Carbon nanotubes are often seen as the only alternative technology to silicon transistors. While they are the most likely short-term alternative, other longer-term alternatives sho...
Hugues Berry, Olivier Temam