Results 31 to 40 of about 1,909,109 (209)
Geometric Primitive-Guided UAV Path Planning for High-Quality Image-Based Reconstruction
Remote Sensing, 2023 Image-based refined 3D reconstruction relies on high-resolution and multi-angle images of scenes. The assistance of multi-rotor drones and gimbal provides great convenience for image acquisition.
Hao Zhou +7 more
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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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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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Submodular Norms with Applications To Online Facility Location and Stochastic Probing [PDF]
, 2023 Optimization problems often involve vector norms, which has led to extensive research on developing algorithms that can handle objectives beyond _p norms.
Russo, Matteo +5 more
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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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Optimal Distributed Submodular Optimization via Sketching [PDF]
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018 We present distributed algorithms for several classes of submodular optimization problems such as k-cover, set cover, facility location, and probabilistic coverage. The new algorithms enjoy almost optimal space complexity, optimal approximation guarantees, optimal communication complexity (and run in only four rounds of computation), addressing major ...
MohammadHossein Bateni +2 more
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Learning and Optimization with Submodular Functions
CoRR, 2015 Tech Report - USC Computer Science CS-599, Convex and Combinatorial ...
Bharath Sankaran +4 more
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Optimal approximation for submodular and supermodular optimization with bounded curvature [PDF]
Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014 We design new approximation algorithms for the problems of optimizing submodular and supermodular functions subject to a single matroid constraint. Specifically, we consider the case in which we wish to maximize a monotone increasing submodular function or minimize a monotone decreasing supermodular function with a bounded total curvature c ...
Sviridenko, M, Vondrák, J, Ward, J
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Minimax Optimization: The Case of Convex-Submodular
CoRR, 2021 Minimax optimization has been central in addressing various applications in machine learning, game theory, and control theory. Prior literature has thus far mainly focused on studying such problems in the continuous domain, e.g., convex-concave minimax optimization is now understood to a significant extent.
Arman Adibi +2 more
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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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