Results 21 to 30 of about 887,365 (205)
Mathematical programming, 2022 We study a family of discrete optimization problems asking for the maximization of the expected value of a concave, strictly increasing, and differentiable function composed with a set-union operator.
Stefano Coniglio +2 more
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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
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Single Machine Vector Scheduling with General Penalties
Mathematics, 2021 In this paper, we study the single machine vector scheduling problem (SMVS) with general penalties, in which each job is characterized by a d-dimensional vector and can be accepted and processed on the machine or rejected.
Xiaofei Liu, Weidong Li, Yaoyu Zhu
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IET Renewable Power Generation, 2023 This paper aims to present an optimization method for the best bus selection (BBS) in the large‐scale power systems in order to send the input signals to the damping controllers.
Mohsen Darabian +2 more
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Constrained Path Search with Submodular Function Maximization
IEEE International Conference on Data Engineering, 2022 In this paper, we study the problem of constrained path search with submodular function maximization (CPS-SM). We aim to find the path with the best submodular function score under a given constraint (e.g., a length limit), where the submodular function ...
Xuefeng Chen +6 more
semanticscholar +1 more source
Approximability of Monotone Submodular Function Maximization under Cardinality and Matroid Constraints in the Streaming Model [PDF]
SIAM Journal on Discrete Mathematics, 2020 Maximizing a monotone submodular function under various constraints is a classical and intensively studied problem. However, in the single-pass streaming model, where the elements arrive one by one and an algorithm can store only a small fraction of ...
Chien-Chung Huang +3 more
semanticscholar +1 more source
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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A Min-Max . . . Functions and Its Implications [PDF]
, 2014 A. Huber and V. Kolmogorov (ISCO 2012) introduced a concept of k-submodular function as a generalization of ordinary submodular (set) functions and bisubmodular functions and obtained a min-max theorem for minimization of k-submodular functions.
Satoru Fujishige, Shin-ichi Tanigawa
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SFExt-PGAbs: Two-Stage Summarization Model for Long Document
Jisuanji kexue yu tansuo, 2021 Aiming at the fluency problem of extractive method, the accuracy problem of abstractive method, and the important information missing problem caused by truncating the original document before document encoding, this paper proposes a two-stage long ...
ZHOU Weixiao, LAN Wenfei, XU Zhiming, ZHU Rongbo
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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
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