Feng Luo

Dec 20, 2024 | science.org | Lei Zhou |Xin-Pu Fu |Ruixing Wang |Feng Luo |Chun-Jiang Jia |Jun Li | +2 more

Published In Science AdvancesVolume 10 | Issue 51December 2024Article versionsSubmission historyReceived: 29 June 2024Accepted: 15 November 2024PermissionsRequest permissions for this article. AcknowledgmentsFunding: This work was supported by the National Natural Science Foundation of China (NSFC nos.

Nov 16, 2024 | arxiv.org | Jie Gao |Kevin Lu |Feng Luo |Hongbin Sun

arXiv:2411.10889 (cs) View PDF HTML (experimental) Comments: Subjects: Machine Learning (cs.LG); Machine Learning (stat.ML) Cite as: arXiv:2411.10889 [cs.LG] (or arXiv:2411.10889v1 [cs.LG] for this version) https://doi.org/10.48550/arXiv.2411.10889 Submission history From: Jie Gao [ view email] [v1] Sat, 16 Nov 2024 21:09:38 UTC (2,014 KB) Bibliographic Tools Bibliographic Explorer Toggle Bibliographic Explorer () Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps...

Jul 16, 2024 | mdpi.com | Rongchuan Lv |Wenyu Gao |Feng Luo |Yinan Li

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.

Apr 19, 2024 | onlinelibrary.wiley.com | Junbao Ma |Zhejiang Province |Feng Luo |Chia-Heng Hsiung

Conflict of interests The authors declare no conflict of interest. Supporting Information As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.

Apr 1, 2024 | arxiv.org | Feng Luo

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.