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ICML
2002
IEEE
14 years 6 months ago
Learning to Share Distributed Probabilistic Beliefs
In this paper, we present a general machine learning approach to the problem of deciding when to share probabilistic beliefs between agents for distributed monitoring. Our approac...
Christopher Leckie, Kotagiri Ramamohanarao
ICML
2010
IEEE
13 years 7 months ago
Multiagent Inductive Learning: an Argumentation-based Approach
Multiagent Inductive Learning is the problem that groups of agents face when they want to perform inductive learning, but the data of interest is distributed among them. This pape...
Santiago Ontañón, Enric Plaza
CCGRID
2007
IEEE
14 years 12 days ago
Performance Evaluation in Grid Computing: A Modeling and Prediction Perspective
Experimental performance studies on computer systems, including Grids, require deep understandings on their workload characteristics. The need arises from two important and closel...
Hui Li