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» Improved learning of Bayesian networks
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HUC
2003
Springer
14 years 1 months ago
Inferring High-Level Behavior from Low-Level Sensors
Abstract. We present a method of learning a Bayesian model of a traveler moving through an urban environment. This technique is novel in that it simultaneously learns a unified mo...
Donald J. Patterson, Lin Liao, Dieter Fox, Henry A...
ACL
2008
13 years 9 months ago
Using Adaptor Grammars to Identify Synergies in the Unsupervised Acquisition of Linguistic Structure
Adaptor grammars (Johnson et al., 2007b) are a non-parametric Bayesian extension of Probabilistic Context-Free Grammars (PCFGs) which in effect learn the probabilities of entire s...
Mark Johnson
ICONIP
2010
13 years 6 months ago
Improving Recurrent Neural Network Performance Using Transfer Entropy
Abstract. Reservoir computing approaches have been successfully applied to a variety of tasks. An inherent problem of these approaches, is, however, their variation in performance ...
Oliver Obst, Joschka Boedecker, Minoru Asada
TKDE
2011
176views more  TKDE 2011»
13 years 2 months ago
Experience Transfer for the Configuration Tuning in Large-Scale Computing Systems
—This paper proposes a new strategy, the experience transfer, to facilitate the management of large-scale computing systems. It deals with the utilization of management experienc...
Haifeng Chen, Wenxuan Zhang, Guofei Jiang
KES
2007
Springer
14 years 2 months ago
Predictive and Contextual Feature Separation for Bayesian Metanetworks
Bayesian Networks are proven to be a comprehensive model to describe causal relationships among domain attributes with probabilistic measure of conditional dependency. However, dep...
Vagan Y. Terziyan