Results 21 to 30 of about 9,788 (160)
IEEE Access, 2018 Submodular optimization plays a significant role in combinatorial problems, since it captures the structure of the edge cuts in graphs, the coverage of sets, and so on. Many data mining and machine learning problems can be cast as submodular maximization
Qilian Yu, Li Xu, Shuguang Cui
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Toward Optimal Placement of Spatial Sensors to Detect Poisson-Distributed Targets
IEEE Access, 2023 This paper addresses the challenges of optimally placing a finite number of sensors to detect Poisson-distributed targets in a bounded domain. We seek to rigorously account for uncertainty in the target arrival model throughout the problem.
Mingyu Kim +5 more
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The Limitations of Optimization from Samples [PDF]
, 2016 In this paper we consider the following question: can we optimize objective functions from the training data we use to learn them? We formalize this question through a novel framework we call optimization from samples (OPS).
Balcan Maria-Florina +15 more
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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
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Submodular memetic approximation for multiobjective parallel test paper generation [PDF]
, 2017 Parallel test paper generation is a biobjective distributed resource optimization problem, which aims to generate multiple similarly optimal test papers automatically according to multiple user-specified assessment criteria.
Fong, Alvis C.M. +2 more
core +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
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Two-Layer Network Caching for Different Service Requirements
Future Internet, 2021 Network caching is a technique used to speed-up user access to frequently requested contents in complex data networks. This paper presents a two-layer overlay network caching system for content distribution.
Gianluca Reali, Mauro Femminella
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Stochastic Block-Coordinate Gradient Projection Algorithms for Submodular Maximization
Complexity, 2018 We consider a stochastic continuous submodular huge-scale optimization problem, which arises naturally in many applications such as machine learning.
Zhigang Li +5 more
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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
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Research on caching strategy based on transmission delay in Cell-Free massive MIMO systems
Tongxin xuebao, 2021 To meet the ultra-low latency and ultra-high reliability requirements of users in the future mobile Internet， the wireless caching technology was combined with Cell-Free massive MIMO systems.The caching model was designed based on AP cooperative caching ...
Rui WANG, Min SHEN, Yun HE, Xiangyan LIU
doaj +2 more sources