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KDD
1998
ACM
190views Data Mining» more  KDD 1998»
14 years 24 days ago
Time Series Forecasting from High-Dimensional Data with Multiple Adaptive Layers
This paper describes our work in learning online models that forecast real-valued variables in a high-dimensional space. A 3GB database was collected by sampling 421 real-valued s...
R. Bharat Rao, Scott Rickard, Frans Coetzee
BMCBI
2006
239views more  BMCBI 2006»
13 years 8 months ago
Applying dynamic Bayesian networks to perturbed gene expression data
Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...
Norbert Dojer, Anna Gambin, Andrzej Mizera, Bartek...
ICANN
2001
Springer
14 years 1 months ago
Generalized Relevance LVQ for Time Series
Abstract. An application of the recently proposed generalized relevance learning vector quantization (GRLVQ) to the analysis and modeling of time series data is presented. We use G...
Marc Strickert, Thorsten Bojer, Barbara Hammer
TFS
2008
123views more  TFS 2008»
13 years 8 months ago
Numerical and Linguistic Prediction of Time Series With the Use of Fuzzy Cognitive Maps
Abstract--In this paper, we introduce a novel approach to timeseries prediction realized both at the linguistic and numerical level. It exploits fuzzy cognitive maps (FCMs) along w...
Wojciech Stach, Lukasz A. Kurgan, Witold Pedrycz
BMCBI
2007
172views more  BMCBI 2007»
13 years 8 months ago
Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks
Background: Reverse engineering cellular networks is currently one of the most challenging problems in systems biology. Dynamic Bayesian networks (DBNs) seem to be particularly su...
Fulvia Ferrazzi, Paola Sebastiani, Marco Ramoni, R...