A convex formulation for learning scale-free networks via submodular relaxation
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 formulat
|Collections||ANU Research Publications|
|Source:||NEURAL INFORMATION PROCESSING SYSTEMS. Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012|
|01_Defazio_A_convex_formulation_for_2012.pdf||385.59 kB||Adobe PDF||Request a copy|
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