Results 31 to 40 of about 5,146,266 (215)
Convex Analysis for Minimizing and Learning Submodular Set Functions [PDF]
, 2013 The connections between convexity and submodularity are explored, for purposes of minimizing and learning submodular set functions. First, we develop a novel method for minimizing a particular class of submodular functions, which can be expressed as a
Peter Stobbe, Stobbe, Peter
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Submodular partition functions
Discrete Mathematics, 2009 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Amini, Omid +3 more
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Subquadratic submodular function minimization [PDF]
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017 Submodular function minimization (SFM) is a fundamental discrete optimization problem which generalizes many well known problems, has applications in various fields, and can be solved in polynomial time. Owing to applications in computer vision and machine learning, fast SFM algorithms are highly desirable. The current fastest algorithms [Lee, Sidford,
Deeparnab Chakrabarty +3 more
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Monotone Submodular Maximization over a Matroid via Non-Oblivious Local Search [PDF]
, 2013 We present an optimal, combinatorial 1−1/e approximation algorithm for monotone submodular optimization over a matroid constraint. Compared to the continuous greedy algorithm (Calinescu, Chekuri, Pál and Vondrák, 2008), our algorithm is extremely simple ...
Filmus, Yuval +3 more
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Mathematics, 2021 In this paper, we consider parallel-machine scheduling with release times and submodular penalties (P|rj,reject|Cmax+π(R)), in which each job can be accepted and processed on one of m identical parallel machines or rejected, but a penalty must paid if a ...
Wencheng Wang, Xiaofei Liu
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Concave Aspects of Submodular Functions [PDF]
2020 IEEE International Symposium on Information Theory (ISIT), 2020 Submodular Functions are a special class of set functions, which generalize several information-theoretic quantities such as entropy and mutual information [1]. Submodular functions have subgradients and subdifferentials [2] and admit polynomial-time algorithms for minimization, both of which are fundamental characteristics of convex functions ...
Rishabh K. Iyer, Jeff A. Bilmes
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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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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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Approximation Algorithms for the Submodular Load Balancing with Submodular Penalties
Mathematics, 2020 In this paper, we study the submodular load balancing problem with submodular penalties. The objective of this problem is to balance the load among sets, while some elements can be rejected by paying some penalties. Officially, given an element set V, we
Xiaofei Liu, Peiyin Xing, Weidong Li
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