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» Parametric Process Model Inference
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ICONIP
2009
13 years 5 months ago
Learning Gaussian Process Models from Uncertain Data
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa
ICA
2010
Springer
13 years 6 months ago
Time Series Causality Inference Using Echo State Networks
One potential strength of recurrent neural networks (RNNs) is their – theoretical – ability to find a connection between cause and consequence in time series in an constraint-...
Norbert Michael Mayer, Oliver Obst, Chang Yu-Chen
CIBCB
2005
IEEE
14 years 1 months ago
Feedback Memetic Algorithms for Modeling Gene Regulatory Networks
— In this paper we address the problem of finding gene regulatory networks from experimental DNA microarray data. We focus on the evaluation of the performance of memetic algori...
Christian Spieth, Felix Streichert, Jochen Supper,...
ICIP
2005
IEEE
14 years 9 months ago
Variable module graphs: a framework for inference and learning in modular vision systems
We present a novel and intuitive framework for building modular vision systems for complex tasks such as surveillance applications. Inspired by graphical models, especially factor...
Amit Sethi, Mandar Rahurkar, Thomas S. Huang
ICGI
2004
Springer
14 years 1 months ago
Navigation Pattern Discovery Using Grammatical Inference
We present a method for modeling user navigation on a web site using grammatical inference of stochastic regular grammars. With this method we achieve better models than the previo...
Nikolaos Karampatziakis, Georgios Paliouras, Dimit...