Results 41 to 50 of about 13,203 (237)
Mathematics, 2023 Federated learning is a promising technique in cloud computing and edge computing environments, and designing a reasonable resource allocation scheme for federated learning is particularly important.
Linjie Liu +3 more
doaj +1 more source
Connectivity of submodular functions
Discrete Mathematics, 1992 This paper relates the connectivity of submodular functions \(f\) to that of certain submodular functions which are derived from \(f\). Here the function \(f\) on \(S\) is submodular if \(f(A)+f(B)\geq f(A\cup B)+f(A\cap B)\) for all subsets \(A\) and \(B\) of \(S\).
James G. Oxley, Geoff Whittle
openaire +1 more source
Constrained robust submodular sensor selection with application to multistatic sonar arrays
IET Radar, Sonar & Navigation, 2017 The authors develop a framework to select a subset of sensors from a field in which the sensors have an ingrained independence structure. Given an arbitrary independence pattern, the authors construct a graph that denotes pairwise independence between ...
Thomas Powers +3 more
doaj +1 more source
Submodular Optimization Approach for Entity Summarization in Knowledge Graph Driven by Large Language Models [PDF]
Jisuanji kexue yu tansuoThe continuous expansion of the knowledge graph has made entity summarization a research hotspot. The goal of entity summarization is to obtain a brief description of an entity from large-scale triple-structured facts that describe it.
ZHANG Qi, ZHONG Hao
doaj +1 more source
Fast and exact search for the partition with minimal information loss. [PDF]
PLoS ONE, 2018 In analysis of multi-component complex systems, such as neural systems, identifying groups of units that share similar functionality will aid understanding of the underlying structures of the system.
Shohei Hidaka, Masafumi Oizumi
doaj +1 more source
Greedy Sensor Selection for Weighted Linear Least Squares Estimation Under Correlated Noise
IEEE Access, 2022 Optimization of sensor selection has been studied to monitor complex and large-scale systems with data-driven linear reduced-order modeling. An algorithm for greedy sensor selection is presented under the assumption of correlated noise in the sensor ...
Keigo Yamada +3 more
doaj +1 more source
CoRR, 2017 We start with an overview of a class of submodular functions called SCMMs (sums of concave composed with non-negative modular functions plus a final arbitrary modular). We then define a new class of submodular functions we call {\em deep submodular functions} or DSFs. We show that DSFs are a flexible parametric family of submodular functions that share
Jeffrey A. Bilmes, Wenruo Bai
openaire +2 more sources
Team Composition in PES2018 Using Submodular Function Optimization
IEEE Access, 2019 With the development of computer game technologies, gameplay becomes very realistic in many sports games, therefore providing appealing play experience to game players.
Yifeng Zeng +3 more
doaj +1 more source
International Journal of Distributed Sensor Networks, 2021 In this article, we consider the problem of optimally selecting a subset of transmitters from a transmitter set available to a multiple-input and multiple-output radar network.
Chenggang Wang +3 more
doaj +1 more source
Improved algorithms for submodular function minimization and submodular flow [PDF]
Proceedings of the thirty-second annual ACM symposium on Theory of computing, 2000 Very recently, two groups of researchers independently developed the first combinatorial, strongly polynomial-time algorithms for submodular function minimization (Iwata, Fleischer, Fujishige; and Schrijver). In this paper, we improve on these algorithms and show that the ideas generated in the design of these algorithms are helpful in other contexts ...
Lisa Fleischer, Satoru Iwata 0001
openaire +1 more source