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» Modeling Sensorimotor Learning with Linear Dynamical Systems
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ICML
2006
IEEE
15 years 10 months ago
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
David Wingate, Satinder P. Singh
CVPR
2005
IEEE
15 years 11 months ago
Modeling and Learning Contact Dynamics in Human Motion
We propose a simple model of human motion as a switching linear dynamical system where the switches correspond to contact forces with the ground. This significantly improves the m...
Alessandro Bissacco
ICML
2010
IEEE
14 years 10 months ago
Learning the Linear Dynamical System with ASOS
We develop a new algorithm, based on EM, for learning the Linear Dynamical System model. Called the method of Approximated Second-Order Statistics (ASOS) our approach achieves dra...
James Martens
KDD
2008
ACM
186views Data Mining» more  KDD 2008»
15 years 10 months ago
Cut-and-stitch: efficient parallel learning of linear dynamical systems on smps
Multi-core processors with ever increasing number of cores per chip are becoming prevalent in modern parallel computing. Our goal is to make use of the multi-core as well as multi...
Lei Li, Wenjie Fu, Fan Guo, Todd C. Mowry, Christo...
ICML
2006
IEEE
15 years 10 months ago
Predictive linear-Gaussian models of controlled stochastic dynamical systems
We introduce the controlled predictive linearGaussian model (cPLG), a model that uses predictive state to model discrete-time dynamical systems with real-valued observations and v...
Matthew R. Rudary, Satinder P. Singh