Balancing Privacy and Utility in Split Learning: An Adversarial Channel Pruning-Based Approach by Afnan Alhindi, Saad Al-Ahmadi, Mohamed Maher Ben Ismail

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A Review and Experimental Evaluation on Split Learning by Zhanyi Hu, Tianchen Zhou, Bingzhe Wu, Cen Chen, Yanhao Wang

Subjects: “…split learning…”
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ADF-SL: An Adaptive and Fair Scheme for Smart Learning Task Distribution by Ahmed A. Al-Saedi, Veselka Boeva

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DFL: Dynamic Federated Split Learning in Heterogeneous IoT by Eric Samikwa, Antonio Di Maio, Torsten Braun

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Model split-based data privacy protection method for federated learning by CHEN Ka

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Toward Representing Identical Privacy-Preserving Graph Neural Network via Split Learning by Yiming Fang, Huiyun Jiao, Risheng Huang

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Decentralized EEG-based detection of major depressive disorder via transformer architectures and split learning by Muhammad Umair, Jawad Ahmad, Nada Alasbali, Oumaima Saidani, Muhammad Hanif, Aizaz Ahmad Khattak, Muhammad Shahbaz Khan

Subjects: “…split learning…”
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Survey of split learning data privacy by QIN Yiqun, MA Xiaojing, FU Jiayun, HU Pingyi, XU Peng, JIN Hai

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A Comprehensive Survey on Split-Fed Learning: Methods, Innovations, and Future Directions by Geetabai S. Hukkeri, R. H. Goudar, G. M. Dhananjaya, Vijayalaxmi N. Rathod, Shilpa Ankalaki

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Leveraging Personalized Customer Experiences in Mobile Edge Computing Through Split Learning Using Smart Data-Driven Modeling by V. Vinoth Kumar, K. M. Karthick Raghunath, Iyappan Perumal, K. Manikandan

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Collaborative Split Learning-Based Dynamic Bandwidth Allocation for 6G-Grade TDM-PON Systems by Alaelddin F. Y. Mohammed, Yazan M. Allawi, Eman M. Moneer, Lamia O. Widaa

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Semantic Meta-Split Learning: A TinyML Scheme for Few-Shot Wireless Image Classification by Eslam Eldeeb, Mohammad Shehab, Hirley Alves, Mohamed-Slim Alouini

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TrapMI: A Data Protection Method to Resist Model Inversion Attacks in Split Learning by Hyunsik Na, Daeseon Choi

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Federated Collaborative Learning with Sparse Gradients for Heterogeneous Data on Resource-Constrained Devices by Mengmeng Li, Xin He, Jinhua Chen

Subjects: “…federated split learning…”
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