Results 11 to 20 of about 1,352 (208)
On additive approximate submodularity [PDF]
Theoretical Computer Science, 2022 A real-valued set function is (additively) approximately submodular if it satisfies the submodularity conditions with an additive error. Approximate submodularity arises in many settings, especially in machine learning, where the function evaluation might not be exact.
Flavio Chierichetti +2 more
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Congruence submodularity [PDF]
Discussiones Mathematicae - General Algebra and Applications, 2002 A lattice \(L\) of equivalence relations on a set \(A\neq \emptyset\) is called \(k\)-submodular \((k\geqq 2\) being a positive integer) if for all \(\theta, \phi, \psi \in L\) with \(\theta \subseteq \psi\) the condition \((\theta,\phi,\theta \dots)\cap \psi\subseteq \theta \vee (\phi\vee \psi)\) (where in the brackets on the left side there are \(k\)
Chajda, Ivan, Halaš, Radomír
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On the Non-Submodularity of the Problem of Adding Links to Minimize the Effective Graph Resistance [PDF]
Journal of Graph Algorithms and ApplicationsWe consider the optimisation problem of adding $k$ links to a given network, such that the resulting effective graph resistance is as small as possible.
Massimo A. Achterberg, Robert E. Kooij
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Submodularity beyond submodular energies: Coupling edges in graph cuts [PDF]
CVPR 2011, 2011 We propose a new family of non-submodular global energy functions that still use submodularity internally to couple edges in a graph cut. We show it is possible to develop an efficient approximation algorithm that, thanks to the internal submodularity, can use standard graph cuts as a subroutine.
Jegelka, S., Bilmes, J.
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Submodularity and the travelling salesman problem [PDF]
, 1990 Submodularity and the travelling salesman ...
Herer, Y.
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Distributed Maximization of Submodular and Approximately Submodular Functions [PDF]
2020 59th IEEE Conference on Decision and Control (CDC), 2020 We study the problem of maximizing a submodular function, subject to a cardinality constraint, with a set of agents communicating over a connected graph. We propose a distributed greedy algorithm that allows all the agents to converge to a near-optimal solution to the global maximization problem using only local information and communication with ...
Lintao Ye, Shreyas Sundaram
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CoRR, 2021 It has been well established that first order optimization methods can converge to the maximal objective value of concave functions and provide constant factor approximation guarantees for (non-convex/non-concave) continuous submodular functions. In this work, we initiate the study of the maximization of functions of the form $F(x) = G(x) +C(x)$ over a
Siddharth Mitra +2 more
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SIAM Journal on Discrete Mathematics, 2009 Let $f:{\cal L}\to\mathbb{R}$ be a submodular function on a modular lattice ${\cal L}$; we show that there is a maximal chain ${\cal C}$ in ${\cal L}$ on which the sequence of values of $f$ is minimal among all paths from 0 to 1 in the Hasse diagram of ${\cal L}$, in a certain well-behaved partial order on sequences of reals.
Graham R. Brightwell, Peter Winkler 0001
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On $k$-Submodular Relaxation [PDF]
SIAM Journal on Discrete Mathematics, 2016 11 pages, corrected typos, accepted in SIAM Journal on Discrete ...
Hiroshi Hirai 0001, Yuni Iwamasa
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Learning submodular functions [PDF]
Proceedings of the forty-third annual ACM symposium on Theory of computing, 2011 There has been much interest in the machine learning and algorithmic game theory communities on understanding and using submodular functions. Despite this substantial interest, little is known about their learnability from data. Motivated by applications, such as pricing goods in economics, this paper considers PAC-style learning of submodular ...
Balcan, Maria-Florina +1 more
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