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» Learning Nonlinear Manifolds from Time Series
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NIPS
2007
14 years 11 months ago
Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression
We propose a method for reconstruction of human brain states directly from functional neuroimaging data. The method extends the traditional multivariate regression analysis of dis...
Sennay Ghebreab, Arnold W. M. Smeulders, Pieter W....
CLEIEJ
2007
152views more  CLEIEJ 2007»
14 years 9 months ago
Gene Expression Analysis using Markov Chains extracted from RNNs
Abstract. This paper present a new approach for the analysis of gene expression, by extracting a Markov Chain from trained Recurrent Neural Networks (RNNs). A lot of microarray dat...
Igor Lorenzato Almeida, Denise Regina Pechmann Sim...
ATMOS
2011
261views Optimization» more  ATMOS 2011»
13 years 9 months ago
On the Utilisation of Fuzzy Rule-Based Systems for Taxi Time Estimations at Airports
The primary objective of this paper is to introduce Fuzzy Rule-Based Systems (FRBSs) as a relatively new technology into airport transportation research, with a special emphasis o...
Jun Chen, Stefan Ravizza, Jason A. D. Atkin, Paul ...
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ICRA
2006
IEEE
87views Robotics» more  ICRA 2006»
15 years 3 months ago
Learning to Predict Slip for Ground Robots
— In this paper we predict the amount of slip an exploration rover would experience using stereo imagery by learning from previous examples of traversing similar terrain. To do t...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
KDD
2009
ACM
172views Data Mining» more  KDD 2009»
15 years 2 months ago
Learning dynamic temporal graphs for oil-production equipment monitoring system
Learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. Most previous work focuses on learn...
Yan Liu, Jayant R. Kalagnanam, Oivind Johnsen