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ECSQARU
2005
Springer
15 years 12 months ago
On the Use of Restrictions for Learning Bayesian Networks
In this paper we explore the use of several types of structural restrictions within algorithms for learning Bayesian networks. These restrictions may codify expert knowledge in a g...
Luis M. de Campos, Javier Gomez Castellano
INFOVIS
2003
IEEE
15 years 11 months ago
EdgeLens: An Interactive Method for Managing Edge Congestion in Graphs
An increasing number of tasks require people to explore, navigate and search extremely complex data sets visualized as graphs. Examples include electrical and telecommunication ne...
Nelson Wong, M. Sheelagh T. Carpendale, Saul Green...
FORTE
2010
15 years 7 months ago
Grouping Nodes in Wireless Sensor Networks Using Coalitional Game Theory
Wireless sensor networks are typically ad-hoc networks of resource-constrained nodes; in particular, the nodes are limited in power resources. It can be difficult and costly to rep...
Fatemeh Kazemeyni, Einar Broch Johnsen, Olaf Owe, ...
SARA
2007
Springer
16 years 14 days ago
Active Learning of Dynamic Bayesian Networks in Markov Decision Processes
Several recent techniques for solving Markov decision processes use dynamic Bayesian networks to compactly represent tasks. The dynamic Bayesian network representation may not be g...
Anders Jonsson, Andrew G. Barto
ALT
2007
Springer
16 years 3 months ago
One-Shot Learners Using Negative Counterexamples and Nearest Positive Examples
As some cognitive research suggests, in the process of learning languages, in addition to overt explicit negative evidence, a child often receives covert explicit evidence in form...
Sanjay Jain, Efim B. Kinber