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Submodular set-functions have many applications in combinatorial optimization, as they can be minimized and approximately maximized in polynomial time.
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Combinatorial Optimization: Polyhedra and Efficiency
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S. P. Boyd and L. Vandenberghe · 2004
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A class of submodular functions for document summarization
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Minimizing a sum of submodular functions
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Transforming an arbitrary MinSum problem into a binary one
D. Schlesinger and B. Flach · 2006
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Reflection methods for user-friendly submodular optimization
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Nondifferentiable optimization and polynomial problems
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A fast continuous max-flow approach to non-convex multi-labeling problems
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From MAP to marginals: Variational inference in Bayesian submodular models
J. Djolonga and A. Krause · 2014
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Tightness results for local consistency relaxations in continuous MRFs
Y. Wald and A. Globerson · 2014
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The power of lp relaxation for map inference
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Duality between subgradient and conditional gradient methods
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Scalable variational inference in log-supermodular models
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On the global linear convergence of frank-wolfe optimization variants
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