Results 11 to 20 of about 5,146,266 (215)
Hypergraphs with edge-dependent vertex weights: p-Laplacians and spectral clustering [PDF]
Frontiers in Big Data, 2023 We study p-Laplacians and spectral clustering for a recently proposed hypergraph model that incorporates edge-dependent vertex weights (EDVW). These weights can reflect different importance of vertices within a hyperedge, thus conferring the hypergraph ...
Yu Zhu, Santiago Segarra
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Efficient Streaming Algorithms for Maximizing Monotone DR-Submodular Function on the Integer Lattice [PDF]
Mathematics, 2022 In recent years, the issue of maximizing submodular functions has attracted much interest from research communities. However, most submodular functions are specified in a set function.
Bich-Ngan T. Nguyen +3 more
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Selecting molecules with diverse structures and properties by maximizing submodular functions of descriptors learned with graph neural networks [PDF]
Scientific Reports, 2022 Selecting diverse molecules from unexplored areas of chemical space is one of the most important tasks for discovering novel molecules and reactions. This paper proposes a new approach for selecting a subset of diverse molecules from a given molecular ...
Tomohiro Nakamura +5 more
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Parallel Submodular Function Minimization [PDF]
Advances in Neural Information Processing Systems 36, 2023 We consider the parallel complexity of submodular function minimization (SFM). We provide a pair of methods which obtain two new query versus depth trade-offs a submodular function defined on subsets of $n$ elements that has integer values between $-M$ and $M$.
Deeparnab Chakrabarty +3 more
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Ranking with submodular functions on a budget. [PDF]
Data Min Knowl Discov, 2022 AbstractSubmodular maximization has been the backbone of many important machine-learning problems, and has applications to viral marketing, diversification, sensor placement, and more. However, the study of maximizing submodular functions has mainly been restricted in the context of selecting a set of items.
Zhang G, Tatti N, Gionis A.
europepmc +5 more sources
Maximization of k-Submodular Function with d-Knapsack Constraints Over Sliding Window
Tsinghua Science and TechnologySubmodular function maximization problem has been extensively studied recently. A natural variant of submodular function is k-submodular function, which has many applications in real life, such as influence maximization and sensor placement problem.
Wenqi Wang +4 more
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Horn functions and submodular boolean functions [PDF]
Theoretical Computer Science, 1997 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Oya Ekin, Peter L. Hammer, Uri N. Peled
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Game Theoretic Clustering for Finding Strong Communities [PDF]
EntropyWe address the challenge of identifying meaningful communities by proposing a model based on convex game theory and a measure of community strength. Many existing community detection methods fail to provide unique solutions, and it remains unclear how ...
Chao Zhao, Ali Al-Bashabsheh, Chung Chan
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Maximizing Symmetric Submodular Functions [PDF]
ACM Transactions on Algorithms, 2015 Symmetric submodular functions are an important family of submodular functions capturing many interesting cases, including cut functions of graphs and hypergraphs. Maximization of such functions subject to various constraints receives little attention by current research, unlike similar minimization problems that have been widely studied. In this work,
Moran Feldman
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Test Suite Reduction via Submodular Function Maximization [PDF]
Jisuanji kexue, 2021 As regression testing size and cost increase,test suite reduction becomes more important to promote its efficiency.Du-ring the selection of test suite subset,we are supposed to consider the representativeness and diversity of subset,and apply an ...
WEN Jin, ZHANG Xing-yu, SHA Chao-feng, LIU Yan-jun
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