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PAMI
2008
182views more  PAMI 2008»
13 years 5 months ago
Gaussian Process Dynamical Models for Human Motion
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
Jack M. Wang, David J. Fleet, Aaron Hertzmann
CORR
2008
Springer
189views Education» more  CORR 2008»
13 years 5 months ago
Algorithms for Dynamic Spectrum Access with Learning for Cognitive Radio
We study the problem of dynamic spectrum sensing and access in cognitive radio systems as a partially observed Markov decision process (POMDP). A group of cognitive users cooperati...
Jayakrishnan Unnikrishnan, Venugopal V. Veeravalli
JDCTA
2010
155views more  JDCTA 2010»
13 years 3 days ago
Multi-factor predication of diesel engine by using artificial neural networks
The paper presents an algorithm which combining a neural network observer, it give more flexible and accurate control on the engine operation. In recent year, several researchers ...
Wenyong Xiao
ICML
2004
IEEE
14 years 6 months ago
Learning low dimensional predictive representations
Predictive state representations (PSRs) have recently been proposed as an alternative to partially observable Markov decision processes (POMDPs) for representing the state of a dy...
Matthew Rosencrantz, Geoffrey J. Gordon, Sebastian...
IJON
2008
101views more  IJON 2008»
13 years 5 months ago
Learning dynamics and robustness of vector quantization and neural gas
Various alternatives have been developed to improve the Winner-Takes-All (WTA) mechanism in vector quantization, including the Neural Gas (NG). However, the behavior of these algo...
Aree Witoelar, Michael Biehl, Anarta Ghosh, Barbar...