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A Convex Formulation for Learning Scale-Free Networks via Submodular Relaxation
Published on 2013-01-143401 Views
A key problem in statistics and machine learning is the determination of network structure from data. We consider the case where the structure of the graph to be reconstructed is known to be scale-fre
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Presentation
A Convex Formulation for Learning Scale-Free Networks via Submodular Relaxation00:00
Scale-free: Heavy tailed degree distribution00:01
Key Ideas00:50
Gene network reconstructions02:31