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ML
2010
ACM
151views Machine Learning» more  ML 2010»
13 years 6 months ago
Inductive transfer for learning Bayesian networks
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
INFOCOM
2010
IEEE
13 years 5 months ago
Predictive Blacklisting as an Implicit Recommendation System
A widely used defense practice against malicious traffic on the Internet is to maintain blacklists, i.e., lists of prolific attack sources that have generated malicious activity in...
Fabio Soldo, Anh Le, Athina Markopoulou
ICML
1998
IEEE
14 years 8 months ago
Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm
In this paper, we adopt general-sum stochastic games as a framework for multiagent reinforcement learning. Our work extends previous work by Littman on zero-sum stochastic games t...
Junling Hu, Michael P. Wellman
ECML
2007
Springer
13 years 11 months ago
On Pairwise Naive Bayes Classifiers
Class binarizations are effective methods for improving weak learners by decomposing multi-class problems into several two-class problems. This paper analyzes how these methods can...
Jan-Nikolas Sulzmann, Johannes Fürnkranz, Eyk...
TAICPART
2006
IEEE
134views Education» more  TAICPART 2006»
14 years 1 months ago
Integration Testing of Components Guided by Incremental State Machine Learning
The design of complex systems, e.g., telecom services, is nowadays usually based on the integration of components (COTS), loosely coupled in distributed architectures. When compon...
Keqin Li 0002, Roland Groz, Muzammil Shahbaz