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KDD
1994
ACM
123views Data Mining» more  KDD 1994»
13 years 11 months ago
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
We describe scoring metrics for learning Bayesian networks from a combination of user knowledge and statistical data. We identify two important properties of metrics, which we cal...
David Heckerman, Dan Geiger, David Maxwell Chicker...
JOCN
2010
66views more  JOCN 2010»
13 years 2 months ago
fMRI Activation during Observation of Others' Reach Errors
When exposed to novel dynamical conditions (e.g., externally imposed forces), neurologically intact subjects easily adjust motor commands on the basis of their own reaching errors...
Nicole Malfait, Kenneth F. Valyear, Jody C. Culham...
IJCNN
2007
IEEE
14 years 1 months ago
Adaptive Dynamic Modularity in a Connectionist Model of Context-Dependent Idea Generation
Abstract— Cognitive control - the ability to produce appropriate behavior in complex situations - is a fundamental aspect of intelligence. It is increasingly evident that this co...
Simona Doboli, Ali A. Minai, Vincent R. Brown
ECTEL
2008
Springer
13 years 9 months ago
Knowledge Practices Environment: Design and Application of Technology for Trialogical Learning
Current networked society present learners with challenges that cannot be sufficiently coped with in educational contexts that are characterized by transmission or participation ep...
Patrick Sins, Merja Bauters, Crina Damsa
NCI
2004
185views Neural Networks» more  NCI 2004»
13 years 8 months ago
Hierarchical reinforcement learning with subpolicies specializing for learned subgoals
This paper describes a method for hierarchical reinforcement learning in which high-level policies automatically discover subgoals, and low-level policies learn to specialize for ...
Bram Bakker, Jürgen Schmidhuber