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检索条件"主题词=Linear Programming"
36165 条 记 录,以下是4771-4780 订阅
排序:
A SOLUTION METHOD FOR ARBITRARY POLYHEDRAL CONVEX SET OPTIMIZATION PROBLEMS
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SIAM JOURNAL ON OPTIMIZATION 2025年 第1期35卷 330-346页
作者: Loehne, Andreas Friedrich Schiller Univ Jena Fac Math & Comp Sci D-07737 Jena Germany
We provide a solution method for the polyhedral convex set optimization problem. that is, the problem to minimize a set-valued maping F: (RRq)-R-n paired right arrows with polyhedral convex graph with respect to a set... 详细信息
来源: 评论
Characterization of Constrained Continuous Multiobjective Optimization Problems: A Performance Space Perspective
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IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 2025年 第1期29卷 275-285页
作者: Vodopija, Aljosa Tusar, Tea Filipic, Bogdan Jozef Stefan Inst Dept Intelligent Syst Ljubljana 1000 Slovenia Jozef Stefan Int Postgrad Sch Ljubljana 1000 Slovenia
Constrained multiobjective optimization has gained much interest in the past few years. However, constrained multiobjective optimization problems (CMOPs) are still unsatisfactorily understood. Consequently, the choice... 详细信息
来源: 评论
Multidimensional Scaling Orienting Discriminative Co-Representation Learning
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IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS 2025年 第1期55卷 71-82页
作者: Qin, Zhang Zhang, Yinghui Wang, Hongjun Luo, Zhipeng Li, Chongshou Li, Tianrui Southwest Jiaotong Univ Tangshan Res Inst Tangshan 063000 Peoples R China Chengdu Neusoft Univ Chengdu 611844 Peoples R China Southwest Jiaotong Univ Sch Comp & Artificial Intelligence Chengdu 611756 Peoples R China Minist Educ Engn Res Ctr Sustainable Urban Intelligent Transpo Chengdu 611756 Peoples R China
Co-representation, which co-represents samples and features, has been widely used in various machine learning tasks, such as document clustering, gene expression analysis, and recommendation systems. It not only revea... 详细信息
来源: 评论
Network-Scale Impact of Vegetation Loss on Coverage and Exposure for 5G Networks
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IEEE ACCESS 2025年 13卷 23902-23912页
作者: Schampheleer, Jorn Huss, Anke Deruyck, Margot Univ Ghent IMEC Dept Informat Technol B-9052 Ghent Belgium Univ Utrecht Inst Risk Assessment Sci NL-3584 CS Utrecht Netherlands
This study investigates the effects of vegetation on 5G network performance, with a particular focus on coverage, user exposure, and base station deployment strategies in an urban environment (Utrecht, The Netherlands... 详细信息
来源: 评论
Distributed Randomized Gradient-Free Convex Optimization With Set Constraints Over Time-Varying Weight-Unbalanced Digraphs
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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2025年 第2期12卷 610-622页
作者: Zhu, Yanan Li, Qinghai Li, Tao Wen, Guanghui Nanjing Univ Informat Sci & Technol Sch Automat Nanjing 210044 Peoples R China Southeast Univ Sch Math Dept Syst Sci Nanjing 210096 Peoples R China
This paper explores a class of distributed constrained convex optimization problems where the objective function is a sum of $N$ convex local objective functions. These functions are characterized by local non-smoothn... 详细信息
来源: 评论
Interpreting and Improving Optimal Control Problems With Directional Corrections
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IEEE ROBOTICS AND AUTOMATION LETTERS 2025年 第5期10卷 4986-4993页
作者: Barron, Trevor Zhang, Xiaojing Apple Inc Cupertino CA 95014 USA
Many robotics tasks, such as path planning or trajectory optimization, are formulated as optimal control problems (OCPs). The key to obtaining high performance lies in the design of the OCP's objective function. I... 详细信息
来源: 评论
A Novel Completion Method for Sparse Traffic Data Imputation
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IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE 2025年 第3期17卷 96-108页
作者: Ouyang, Renqiu Hu, Yikun Wang, Haotian Hu, Rong Yang, Wangdong Li, Kenli Hunan Univ Changsha 410082 Peoples R China Hunan Univ Comp Sci & Technol Changsha 410082 Peoples R China
Traffic data imputation is essential in smart cities and the Internet of Things (IoT). Tensor completion is an efficient method for traffic data imputation. However, these methods overlook the integration of contextua... 详细信息
来源: 评论
POSES: Patch Optimization Strategies for Efficiency and Stealthiness Using eXplainable AI
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IEEE ACCESS 2025年 13卷 57166-57176页
作者: Lee, Han-Ju Kim, Jin-Seoung Lee, Han-Jin Choi, Seok-Hwan Yonsei Univ Div Software Wonju Si 26493 Gangwon Do South Korea
Adversarial examples, which are carefully crafted inputs designed to deceive deep learning models, create significant challenges in Artificial Intelligence. While adversarial examples have primarily focused on digital... 详细信息
来源: 评论
Fast Data-Driven Greedy Sensor Selection for Ridge Regression
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IEEE SENSORS JOURNAL 2025年 第6期25卷 10030-10045页
作者: Sasaki, Yasuo Yamada, Keigo Nagata, Takayuki Saito, Yuji Nonomura, Taku Nagoya Univ Dept Aerosp Engn Nagoya 4648603 Japan Tohoku Univ Dept Aerosp Engn Sendai 9808579 Japan Tohoku Univ Frontier Res Inst Interdisciplinary Sci Sendai 9808578 Japan
We propose a data-driven sensor-selection algorithm for accurate estimation of the target variables from the selected measurements. The target variables are assumed to be estimated by a ridge-regression estimator, whi... 详细信息
来源: 评论
Decentralized and Communication-Based Multi-Agent Traffic Signal Control Model Employing a Graph Representation for the State
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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2025年 第5期26卷 5947-5960页
作者: Yoon, Jinwon Ahn, Kyuree Lee, Kanghoon Park, Jinkyoo Yeo, Hwasoo Korea Adv Inst Sci & Technol Daejeon 34141 South Korea Omelet Daejeon 34051 South Korea
Reinforcement learning (RL) has emerged as an effective approach for signal control, and several studies attempt to apply RL to network-wide signal control problems. Most existing methods for network-wide signal contr... 详细信息
来源: 评论