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NN
2006
Springer
13 years 8 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
CAS
2005
109views more  CAS 2005»
13 years 7 months ago
Bringing Up Robot: Fundamental Mechanisms For Creating A Self-Motivated, Self-Organizing Architecture
In this paper we propose an intrinsic developmental algorithm that is designed to allow a mobile robot to incrementally progress through levels of increasingly sophisticated behav...
Douglas S. Blank, Deepak Kumar, Lisa Meeden, James...
NN
2000
Springer
161views Neural Networks» more  NN 2000»
13 years 7 months ago
How good are support vector machines?
Support vector (SV) machines are useful tools to classify populations characterized by abrupt decreases in density functions. At least for one class of Gaussian data model the SV ...
Sarunas Raudys
ICANN
2011
Springer
12 years 11 months ago
Learning from Multiple Annotators with Gaussian Processes
Abstract. In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, po...
Perry Groot, Adriana Birlutiu, Tom Heskes
ICAISC
2004
Springer
14 years 1 months ago
Semi-mechanistic Models for State-Estimation - Soft Sensor for Polymer Melt Index Prediction
Nonlinear state estimation is a useful approach to the monitoring of industrial (polymerization) processes. This paper investigates how this approach can be followed to the develop...
Balazs Feil, János Abonyi, Peter Pach, Sand...