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A Convex Formulation for Learning Scale-Free Networks via Submodular Relaxation
Aaron Defazio
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Oznake: computer science;optimization methods;convex optimization;machine learning;supervised learning
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-free. We show that in such cases it is natural to formulate structured sparsity inducing priors using s ...
Leto: 2012 Vir: videolectures.net
Št. zadetkov: 1
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