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» Learning Nonlinear Dynamic Models from Non-sequenced Data
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ICML
2007
IEEE
14 years 8 months ago
Recovering temporally rewiring networks: a model-based approach
A plausible representation of relational information among entities in dynamic systems such as a living cell or a social community is a stochastic network which is topologically r...
Fan Guo, Steve Hanneke, Wenjie Fu, Eric P. Xing
ICANN
2001
Springer
14 years 2 days 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
FSS
2010
147views more  FSS 2010»
13 years 6 months ago
A divide and conquer method for learning large Fuzzy Cognitive Maps
Fuzzy Cognitive Maps (FCMs) are a convenient tool for modeling and simulating dynamic systems. FCMs were applied in a large number of diverse areas and have already gained momentu...
Wojciech Stach, Lukasz A. Kurgan, Witold Pedrycz
ICPR
2008
IEEE
14 years 8 months ago
Incremental learning in non-stationary environments with concept drift using a multiple classifier based approach
We outline an incremental learning algorithm designed for nonstationary environments where the underlying data distribution changes over time. With each dataset drawn from a new e...
Matthew T. Karnick, Michael Muhlbaier, Robi Polika...
GECCO
2005
Springer
180views Optimization» more  GECCO 2005»
14 years 1 months ago
Inference of gene regulatory networks using s-system and differential evolution
In this work we present an improved evolutionary method for inferring S-system model of genetic networks from the time series data of gene expression. We employed Differential Ev...
Nasimul Noman, Hitoshi Iba