Quantum and classical algorithms for approximate submodular function minimization
نویسندگان
چکیده
منابع مشابه
Geometric Rescaling Algorithms for Submodular Function Minimization
We present a new class of polynomial-time algorithms for submodular function minimization (SFM), as well as a unified framework to obtain strongly polynomial SFM algorithms. Our new algorithms are based on simple iterative methods for the minimum-norm problem, such as the conditional gradient and the Fujishige-Wolfe algorithms. We exhibit two techniques to turn simple iterative methods into pol...
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This survey describes the submodular function minimization problem (SFM); why it is important; techniques for solving it; algorithms by Cunningham [7, 11, 12], by Schrijver [69] as modified by Fleischer and Iwata [20], by Orlin [64], by Iwata, Fleischer, and Fujishige [45], and by Iwata [41, 43] for solving it; and extensions of SFM to more general families of subsets.
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A set function f defined on the subsets of a finite set V is said to be submodular if it satisfies f(X) + f(Y ) ≥ f(X ∪ Y ) + f(X ∩ Y ), ∀X, Y ⊆ V. Submodular functions are discrete analogues of convex functions. They arise in various branches of applied mathematics such as game theory, information theory, and queueing theory. Examples include the matroid rank functions, the cut capacity functi...
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ژورنال
عنوان ژورنال: Quantum Information and Computation
سال: 2019
ISSN: 1533-7146,1533-7146
DOI: 10.26421/qic19.15-16-5