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» Approximate Learning of Dynamic Models
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FSS
2010
147views more  FSS 2010»
15 years 3 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
199
Voted
AAMAS
2005
Springer
15 years 5 months ago
Cooperative Multi-Agent Learning: The State of the Art
Cooperative multi-agent systems are ones in which several agents attempt, through their interaction, to jointly solve tasks or to maximize utility. Due to the interactions among t...
Liviu Panait, Sean Luke
163
Voted
CORR
2010
Springer
183views Education» more  CORR 2010»
15 years 3 months ago
Discovering shared and individual latent structure in multiple time series
This paper proposes a nonparametric Bayesian method for exploratory data analysis and feature construction in continuous time series. Our method focuses on understanding shared fe...
Suchi Saria, Daphne Koller, Anna Penn
ICANN
2009
Springer
15 years 9 months ago
An EM Based Training Algorithm for Recurrent Neural Networks
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
Jan Unkelbach, Yi Sun, Jürgen Schmidhuber
CDC
2008
IEEE
110views Control Systems» more  CDC 2008»
15 years 11 months ago
Multistage investments with recourse: A single-asset case with transaction costs
— We consider a financial decision problem involving dynamic investment decisions on a single risky instrument over multiple and discrete time periods. Investment returns are as...
Ufuk Topcu, Giuseppe Carlo Calafiore, Laurent El G...