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» Learning Qualitative Models of Dynamic Systems
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GECCO
2005
Springer
204views Optimization» more  GECCO 2005»
14 years 3 months ago
Modeling systems with internal state using evolino
Existing Recurrent Neural Networks (RNNs) are limited in their ability to model dynamical systems with nonlinearities and hidden internal states. Here we use our general framework...
Daan Wierstra, Faustino J. Gomez, Jürgen Schm...
NIPS
1993
13 years 11 months ago
Using Local Trajectory Optimizers to Speed Up Global Optimization in Dynamic Programming
Dynamic programming provides a methodology to develop planners and controllers for nonlinear systems. However, general dynamic programming is computationally intractable. We have ...
Christopher G. Atkeson
IJCNN
2007
IEEE
14 years 4 months ago
Integrating a Flexible Representation Machinery in a Model of Human Concept Learning
— High-order human cognition involves processing of abstract and categorically represented knowledge. Traditionally, it has been considered that there is a single innate internal...
Toshihiko Matsuka, Yasuaki Sakamoto
IJCNN
2007
IEEE
14 years 4 months ago
Adaptive Dynamic Modularity in a Connectionist Model of Context-Dependent Idea Generation
Abstract— Cognitive control - the ability to produce appropriate behavior in complex situations - is a fundamental aspect of intelligence. It is increasingly evident that this co...
Simona Doboli, Ali A. Minai, Vincent R. Brown
PAMI
2008
161views more  PAMI 2008»
13 years 9 months ago
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models
The Expectation Maximization (EM) algorithm is widely used for learning finite mixture models despite its greedy nature. Most popular model-based clustering techniques might yield...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...