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Fast Semidifferential-based Submodular Function Optimization
[article]
2013
arXiv
pre-print
We present a practical and powerful new framework for both unconstrained and constrained submodular function optimization based on discrete semidifferentials (sub- and super-differentials). The resulting algorithms, which repeatedly compute and then efficiently optimize submodular semigradients, offer new and generalize many old methods for submodular optimization. Our approach, moreover, takes steps towards providing a unifying paradigm applicable to both submodular min- imization and
arXiv:1308.1006v1
fatcat:zyenz2okerbstmjyqkl43azsy4