Abstract
Chapter 4 focuses on the expressive power of binary submodular functions. Known and new classes of submodular functions that are expressible by binary submodular functions are presented. There is a close relationship between the expressive power of binary submodular functions and solving submodular valued constraint satisfaction problems via the minimum cut problem: showing that a class \(\mathcal{C}\) of submodular functions is expressible by binary submodular functions is equivalent to showing that functions from \(\mathcal{C}\) can be minimised efficiently via the minimum cut problem.
An algorithm must be seen to be believed.
Donald Knuth
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Notes
- 1.
- 2.
Note that this result is not obvious because simply changing the infinite cost to some big, but finite constant M does not work: for c 1<c 2, ∞+c 1≥∞+c 2, but M+c 1<M+c 2. For instance, consider the submodular cost function ϕ defined as follows: ϕ(0,0)=ϕ(1,0)=∞, ϕ(0,1)=1, and ϕ(1,1)=2. Changing ϕ(0,0)=ϕ(1,0)=M for any finite number M would violate the submodularity condition.
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- 4.
Most papers on pseudo-Boolean optimisation deal with the maximisation problem, and therefore talk about supermodular functions, rather than submodular functions. However, the maximisation problem of supermodular functions is equivalent to the minimisation problem of submodular functions.
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Živný, S. (2012). Expressibility of Submodular Languages. In: The Complexity of Valued Constraint Satisfaction Problems. Cognitive Technologies. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33974-5_4
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