Results 1 to 10 of about 13,098 (239)
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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Weakly Submodular Functions [PDF]
, 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
Allan Borodin, Dai Le, Yuli Ye
core +5 more sources
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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Resilient Monotone Submodular Function Maximization [PDF]
2017 IEEE 56th Annual Conference on Decision and Control (CDC), 2017 In this paper, we focus on applications in machine learning, optimization, and control that call for the resilient selection of a few elements, e.g. features, sensors, or leaders, against a number of adversarial denial-of-service attacks or failures.
Gatsis, Konstantinos +3 more
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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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Maximizing Symmetric Submodular Functions [PDF]
ACM Transactions on Algorithms, 2016 Symmetric submodular functions are an important family of submodular functions capturing many interesting cases including cut functions of graphs and hypergraphs.
Feldman, Moran
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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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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
doaj +2 more sources