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Kongyang Chen

As seen in: Nature, arXiv, MDPI
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Articles by Kongyang Chen

Research on overhead transmission line planning based on an improved A* algorithm

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By Kongyang Chen, Xiaodong Ma, Rui Guo, Lei Pan, Zhihong Sun, Zhenhai Zhou
| Nature Verified
Abstract Efficient route planning for overhead transmission lines is crucial for reducing construction costs, ensuring operational safety, and improving environmental adaptability.
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Computer Science > Distributed, Parallel, and Cluster Computing

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By Kongyang Chen, Tiancai Liang
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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Computer Science > Cryptography and Security

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By Kongyang Chen, Yao Huang, Yuanwei Guo
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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Leveraging Federated Learning for Malware Classification: A Heterogeneous Integration Approach

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By Kongyang Chen, Wangjun Zhang, Zhangmao Liu
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Multi-Party Data Pricing for Complex Data Trading Markets: A Rubinstein Bargaining Approach

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By Kongyang Chen, Zhengwang Han
| arXiv
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TIBW: Task-Independent Backdoor Watermarking with Fine-Tuning Resilience for Pre-Trained Language Models

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By Kongyang Chen, Weichuan Mo, Yatie Xiao
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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[2405.07317] Machine Unlearning in Contrastive Learning

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By Kongyang Chen
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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[2404.15278] Security-Sensitive Task Offloading in Integrated Satellite-Terrestrial Networks

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By Kongyang Chen, Jiannong Cao, Yikai Li, Ning Li
| arXiv
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Fast and Accurate SNN Model Strengthening for Industrial Applications

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By Weitong Chen, Kongyang Chen, Deming Zhou
| MDPI
Article Menu /ajax/scifeed/subscribe Altmetric announcement Help format_quote Cite thumb_up ... Endorse Need Help? Find support for a specific problem in the support section of our website. Please let us know what you think of our products and services. Visit our dedicated information section to learn more about MDPI.
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[2306.17183] Deep Reinforcement Learning for Privacy-Preserving Task Offloading in Integrated Satellite-Terrestrial Networks

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By Yikai Li, Kongyang Chen, Jiannong Cao, Yuvraj Sahni
| arXiv
arXiv:2306.17183 (cs) Download a PDF of the paper titled Deep Reinforcement Learning for Privacy-Preserving Task Offloading in Integrated Satellite-Terrestrial Networks, by Wenjun Lan and 4 other authors Download PDF Submission history From: Kongyang Chen [ view email] [v1] Tue, 20 Jun 2023 07:30:12 UTC (571 KB) Bibliographic Tools Bibliographic Explorer Toggle Bibliographic Explorer () Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?)...
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