Results 81 to 90 of about 10,146,366 (200)
Data Correcting Algorithms in Combinatorial Optimization [PDF]
This paper describes data correcting algorithms. It provides the theory behind the algorithms and presents the implementation details and computational experience with these algorithms on the asymmetric traveling salesperson problem, the problem of ...
Goldengorin, Boris +2 more
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Online submodular set cover, ranking, and repeated active learning [PDF]
, 2011 We propose an online prediction version of submodular set cover with connections to ranking and repeated active learning. In each round, the learning algorithm chooses a sequence of items.
Andrew Guillory, Jeff Bilmes
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Expected Maximization of a Concave Utility Function Under Threshold-Based Activation
AxiomsMaximizing the expected value of a concave and strictly increasing utility function defines a fundamental class of discrete optimization problems. Among them, coverage decision problems with diminishing marginal returns under uncertainty, typically ...
Guangming Li +4 more
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Maximizing General Set Functions by Submodular Decomposition
, 2009 We present a branch and bound method for maximizing an arbitrary set function h mapping 2^V to R. By decomposing h as f-g, where f is a submodular function and g is the cut function of a (simple, undirected) graph G with vertex set V, our original problem is reduced to a sequence of submodular maximization problems.
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Quotient-convergence of Submodular Setfunctions [PDF]
We introduce the concept of quotient-convergence for sequences of submodular set functions, providing, among others, a new framework for the study of convergence of matroids through their rank functions.
Bérczi, Kristóf +3 more
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A Mazur-Orlicz type theorem for submodular set functions
Journal of Mathematical Analysis and Applications, 1986 Let \({\mathcal L}\) be a lattice of subsets of a given set \(\Omega\) with \(\emptyset \in {\mathcal L}\). A function \(\gamma:{\mathcal L}\to {\mathbb{R}}\cup \{- \infty \}\) is called a submodular (modular) set function if \(\gamma (\emptyset)=0\) and \[ \gamma (A\cup B)+\gamma (A\cap B)\leq (=)\gamma (A)+\gamma (B),\quad A\in {\mathcal L},\quad B ...
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Journal of Numerical Analysis and Approximation Theory, 2018 In this paper, for the univariate Bernstein-Kantorovich-Choquet, Szasz-Kantorovich-Choquet, Baskakov-Kantorovich-Choquet and Bernstein-Durrmeyer-Choquet operators written in terms of the Choquet integrals with respect to monotone and submodular set ...
Sorin Gal
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Balanced sets in an independence structure induced by a submodular function
Journal of Mathematical Analysis and Applications, 1983 AbstractA submodular (and non-decreasing) function on a set induces an independence structure; the notion of a “balanced” set in this situation helps us determine whether a given independence structure is induced by any submodular function other than its own rank function, answering a question of U. S. R. Murty and I. Simon.
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Data Summarization beyond Monotonicity: Non-monotone Two-Stage Submodular Maximization [PDF]
, 2023 The objective of a two-stage submodular maximization problem is to reduce the ground set using provided training functions that are submodular, with the aim of ensuring that optimizing new objective functions over the reduced ground set yields results ...
Tang, Shaojie
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The submodular knapsack polytope
, 2009 The submodular knapsack set is the discrete lower level set of a submodular function. The modular case reduces to the classical linear 0–1 knapsack set.
ATAMTURK, A, NARAYANAN, V
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