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» Variational methods for Reinforcement Learning
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SDM
2009
SIAM
220views Data Mining» more  SDM 2009»
14 years 4 months ago
Bayesian Cluster Ensembles.
Cluster ensembles provide a framework for combining multiple base clusterings of a dataset to generate a stable and robust consensus clustering. There are important variants of th...
Hongjun Wang, Hanhuai Shan, Arindam Banerjee
ICML
2010
IEEE
13 years 8 months ago
Continuous-Time Belief Propagation
Many temporal processes can be naturally modeled as a stochastic system that evolves continuously over time. The representation language of continuous-time Bayesian networks allow...
Tal El-Hay, Ido Cohn, Nir Friedman, Raz Kupferman
ICASSP
2010
IEEE
13 years 7 months ago
Image-quality prediction of synthetic aperture sonar imagery
This work exploits several machine-learning techniques to address the problem of image-quality prediction of synthetic aperture sonar (SAS) imagery. The objective is to predict th...
David P. Williams
CE
2005
71views more  CE 2005»
13 years 7 months ago
Teachers' pedagogical designs for technology-supported collective inquiry: A national case study
The aim of the present study was to analyze teachers' pedagogical designs, plans of organized technology-supported, collective student inquiry. Ten teachers in Finland design...
Minna Lakkala, Jiri Lallimo, Kai Hakkarainen
IJCNN
2008
IEEE
14 years 2 months ago
Incremental Common Spatial Pattern algorithm for BCI
— A major challenge in applying machine learning methods to Brain-Computer Interfaces (BCIs) is to overcome the on-line non-stationarity of the data blocks. An effective BCI syst...
Qibin Zhao, Liqing Zhang, Andrzej Cichocki, Jie Li