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MCS
2009
Springer
14 years 1 days ago
Regularized Linear Models in Stacked Generalization
Abstract. Stacked generalization is a flexible method for multiple classifier combination; however, it tends to overfit unless the combiner function is sufficiently smooth. Prev...
Samuel Robert Reid, Gregory Z. Grudic
ENGL
2007
204views more  ENGL 2007»
13 years 7 months ago
Long-Term Prediction, Chaos and Artificial Neural Networks. Where is the Meeting Point?
—This paper presents the advances of a research using a combination of recurrent and feed-forward neural networks for long term prediction of chaotic time series. It is known tha...
Pilar Gómez-Gil
CADE
2007
Springer
14 years 7 months ago
Combination Methods for Satisfiability and Model-Checking of Infinite-State Systems
Manna and Pnueli have extensively shown how a mixture of first-order logic (FOL) and discrete Linear time Temporal Logic (LTL) is sufficient to precisely state verification problem...
Silvio Ghilardi, Enrica Nicolini, Silvio Ranise, D...
INFOCOM
2005
IEEE
14 years 1 months ago
Predicting Internet end-to-end delay: a multiple-model approach
This paper presents a novel approach to predict the Internet end-to-end delay using multiple-model (MM) methods. The basic idea of the MM method is to assume the system dynamics c...
Ming Yang, Jifeng Ru, X. Rong Li, Huimin Chen, Anw...
TMI
2008
136views more  TMI 2008»
13 years 7 months ago
Classification of fMRI Time Series in a Low-Dimensional Subspace With a Spatial Prior
We propose a new method for detecting activation in functional magnetic resonance imaging (fMRI) data. We project the fMRI time series on a low-dimensional subspace spanned by wave...
François G. Meyer, Xilin Shen