Results 41 to 50 of about 2,699,353 (198)
Hardness of submodular cost allocation : lattice matching and a simplex coloring conjecture [PDF]
, 2014 We consider the Minimum Submodular Cost Allocation (MSCA) problem. In this problem, we are given k submodular cost functions f1, ... , fk: 2V -> R+ and the goal is to partition V into k sets A1, ..., Ak so as to minimize the total cost sumi = 1,k fi(Ai).
Vondrák, Jan, Ene, Alina
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Submodular Functions are Noise Stable [PDF]
Proceedings of the Twenty-Third Annual ACM-SIAM Symposium on Discrete Algorithms, 2012 We show that all non-negative submodular functions have high {\em noise-stability}. As a consequence, we obtain a polynomial-time learning algorithm for this class with respect to any product distribution on $\{-1,1\}^n$ (for any constant accuracy parameter $ε$). Our algorithm also succeeds in the agnostic setting.
Mahdi Cheraghchi +3 more
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Reconfiguration Problems on Submodular Functions [PDF]
Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining, 2022 Reconfiguration problems require finding a step-by-step transformation between a pair of feasible solutions for a particular problem. The primary concern in Theoretical Computer Science has been revealing their computational complexity for classical problems.
Naoto Ohsaka, Tatsuya Matsuoka
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Submodular stochastic probing on matroids [PDF]
, 2014 In a stochastic probing problem we are given a universe E, where each element e in E is active independently with probability p in [0,1], and only a probe of e can tell us whether it is active or not. On this universe we execute a process that one by one
Sviridenko, Maxim +5 more
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CoRR, 2014 Submodular functions are well-studied in combinatorial optimization, game theory and economics. The natural diminishing returns property makes them suitable for many applications. We study an extension of monotone submodular functions, which we call {\em weakly submodular functions}. Our extension includes some (mildly) supermodular functions.
Allan Borodin, Dai Le, Yuli Ye
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Approximate Representation of Symmetric Submodular Functions via Hypergraph Cut Functions [PDF]
, 2022 Submodular functions are fundamental to combinatorial optimization. Many interesting problems can be formulated as special cases of problems involving submodular functions.
Chekuri, Chandra +3 more
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Stochastic Block-Coordinate Gradient Projection Algorithms for Submodular Maximization
Complexity, 2018 We consider a stochastic continuous submodular huge-scale optimization problem, which arises naturally in many applications such as machine learning.
Zhigang Li +5 more
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On the Reducibility of Submodular Functions
CoRR, 2016 The scalability of submodular optimization methods is critical for their usability in practice. In this paper, we study the reducibility of submodular functions, a property that enables us to reduce the solution space of submodular optimization problems without performance loss. We introduce the concept of reducibility using marginal gains.
Jincheng Mei, Hao Zhang, Bao-Liang Lu
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Monotonic decompositions of submodular set functions [PDF]
Submodular set functions are undoubtedly among the most important building blocks of combinatorial optimization. Somewhat surprisingly, continuous counterparts of such functions have also appeared in an analytic line of research where they found ...
Imolay, András +4 more
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Constrained robust submodular sensor selection with application to multistatic sonar arrays
IET Radar, Sonar & Navigation, 2017 The authors develop a framework to select a subset of sensors from a field in which the sensors have an ingrained independence structure. Given an arbitrary independence pattern, the authors construct a graph that denotes pairwise independence between ...
Thomas Powers +3 more
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