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» Improved learning of Bayesian networks
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HUC
2003
Springer
15 years 8 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...
118
Voted
ACL
2008
15 years 4 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
127
Voted
ICONIP
2010
15 years 1 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»
14 years 10 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
15 years 9 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