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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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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Curvature and Optimal Algorithms for Learning and Minimizing Submodular Functions [PDF]
, 2013 We investigate three related and important problems connected to machine learning: approximating a submodular function everywhere, learning a submodular function (in a PAC-like setting [53]), and constrained minimization of submodular functions.
Rishabh Iyer +2 more
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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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New Query Lower Bounds for Submodular Function MInimization [PDF]
, 2019 We consider submodular function minimization in the oracle model: given black-box access to a submodular set function $f:2^{[n]}\rightarrow \mathbb{R}$, find an element of $\arg\min_S \{f(S)\}$ using as few queries to $f(\cdot)$ as possible. State-of-the-
Andrei Graur +3 more
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Weakly Submodular Functions [PDF]
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
Borodin, Allan +2 more
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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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On Equivalence of M$^\natural$-concavity of a Set Function and Submodularity of Its Conjugate [PDF]
, 2017 A fundamental theorem in discrete convex analysis states that a set function is M$^\natural$-concave if and only if its conjugate function is submodular.
Kazuo Murota, Akiyoshi Shioura
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Analyzing greedy vaccine allocation algorithms for metapopulation disease models. [PDF]
PLoS Computational BiologyAs observed in the case of COVID-19, effective vaccines for an emerging pandemic tend to be in limited supply initially and must be allocated strategically.
Jeffrey Keithley +3 more
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Link-based influence maximization in networks of health promotion professionals. [PDF]
PLoS ONE, 2021 The influence maximization problem (IMP) as classically formulated is based on the strong assumption that "chosen" nodes always adopt the new product. In this paper we propose a new influence maximization problem, referred to as the "Link-based Influence
Maurits H W Oostenbroek +4 more
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