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Efficient Federated Learning with Heterogeneous Data and Adaptive Dropout.

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Title: Efficient Federated Learning with Heterogeneous Data and Adaptive Dropout.
Authors: Liu, Ji1, jiliuwork@gmail.com, Ma, Beichen2, bm685@cornell.edu, Yu, Qiaolin3, qy254@cornell.edu, Jin, Ruoming4, rjin1@kent.edu, Zhou, Jingbo5, zhoujingbo@outlook.com, Zhou, Yang6, yangzhou@auburn.edu, Dai, Huaiyu7, hdai@ncsu.edu, Wang, Haixun8, haixun@gmail.com, Dou, Dejing9, dejingdou@gmail.com, Valduriez, Patrick10, patrick.valduriez@inria.fr
Source: ACM Transactions on Knowledge Discovery from Data; Sep2025, Vol. 19 Issue 8, p1-31, 31p
Database: Applied Science & Technology Source
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  Data: <searchLink fieldCode="AU" term="%22Liu%2C+Ji%22">Liu, Ji</searchLink><relatesTo>1</relatesTo>, <i>jiliuwork@gmail.com</i><br /><searchLink fieldCode="AU" term="%22Ma%2C+Beichen%22">Ma, Beichen</searchLink><relatesTo>2</relatesTo>, <i>bm685@cornell.edu</i><br /><searchLink fieldCode="AU" term="%22Yu%2C+Qiaolin%22">Yu, Qiaolin</searchLink><relatesTo>3</relatesTo>, <i>qy254@cornell.edu</i><br /><searchLink fieldCode="AU" term="%22Jin%2C+Ruoming%22">Jin, Ruoming</searchLink><relatesTo>4</relatesTo>, <i>rjin1@kent.edu</i><br /><searchLink fieldCode="AU" term="%22Zhou%2C+Jingbo%22">Zhou, Jingbo</searchLink><relatesTo>5</relatesTo>, <i>zhoujingbo@outlook.com</i><br /><searchLink fieldCode="AU" term="%22Zhou%2C+Yang%22">Zhou, Yang</searchLink><relatesTo>6</relatesTo>, <i>yangzhou@auburn.edu</i><br /><searchLink fieldCode="AU" term="%22Dai%2C+Huaiyu%22">Dai, Huaiyu</searchLink><relatesTo>7</relatesTo>, <i>hdai@ncsu.edu</i><br /><searchLink fieldCode="AU" term="%22Wang%2C+Haixun%22">Wang, Haixun</searchLink><relatesTo>8</relatesTo>, <i>haixun@gmail.com</i><br /><searchLink fieldCode="AU" term="%22Dou%2C+Dejing%22">Dou, Dejing</searchLink><relatesTo>9</relatesTo>, <i>dejingdou@gmail.com</i><br /><searchLink fieldCode="AU" term="%22Valduriez%2C+Patrick%22">Valduriez, Patrick</searchLink><relatesTo>10</relatesTo>, <i>patrick.valduriez@inria.fr</i>
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              Text: Sep2025
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