A General Framework For Task-Oriented Network Inference Article Swipe
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Inference
Computer science
Maximization
Task (project management)
Statement (logic)
Problem statement
Network structure
Space (punctuation)
Artificial intelligence
Theoretical computer science
Mathematical optimization
Management science
Mathematics
Engineering
Political science
Law
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Ivan Brugere
,
Chris Kanich
,
Tanya Berger‐Wolf
·
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1705.00645
· OA: W2611113433
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1705.00645
· OA: W2611113433
We present a brief introduction to a flexible, general network inference framework which models data as a network space, sampled to optimize network structure to a particular task. We introduce a formal problem statement related to influence maximization in networks, where the network structure is not given as input, but learned jointly with an influence maximization solution.
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