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Lingjuan Lyu

Showing results (1-10 of 10) with videos related to

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Advances in Neural Information Processing Systems|May 8, 2023
Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source SamplingJunyuan Hong, Lingjuan Lyu, Jiayu Zhou, et al.
Nature Communications|April 20, 2022
Communication-efficient federated learning via knowledge distillationChuhan Wu, Fangzhao Wu, Lingjuan Lyu, et al.
Proceedings of Machine Learning Research|April 30, 2025
Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity LearningJiaqi Wang, Chenxu Zhao, Lingjuan Lyu, et al.
Nature Communications|June 2, 2022
A federated graph neural network framework for privacy-preserving personalizationChuhan Wu, Fangzhao Wu, Lingjuan Lyu, et al.
IEEE Transactions on Neural Networks and Learning Systems|May 16, 2025
SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End DevicesZhengyi Zhong, Weidong Bao, Ji Wang, et al.
IEEE Transactions on Neural Networks and Learning Systems|April 7, 2023
InOR-Net: Incremental 3-D Object Recognition Network for Point Cloud RepresentationJiahua Dong, Yang Cong, Gan Sun, et al.
Patterns (New York, N.Y.)|January 8, 2025
Integration of large language models and federated learningChaochao Chen, Xiaohua Feng, Yuyuan Li, et al.
IEEE Transactions on Neural Networks and Learning Systems|October 29, 2021
Joint Stance and Rumor Detection in Hierarchical Heterogeneous GraphChen Li, Hao Peng, Jianxin Li, et al.
IEEE Transactions on Neural Networks and Learning Systems|November 10, 2022
Privacy and Robustness in Federated Learning: Attacks and DefensesLingjuan Lyu, Han Yu, Xingjun Ma, et al.
Nature Communications|February 21, 2026
Auditing unauthorized training data from AI generated content using information isotopesTao Qi, Jinhua Yin, Dongqi Cai, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
Advances in Neural Information Processing Systems|May 8, 2023
Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source SamplingJunyuan Hong, Lingjuan Lyu, Jiayu Zhou, et al.
Nature Communications|April 20, 2022
Communication-efficient federated learning via knowledge distillationChuhan Wu, Fangzhao Wu, Lingjuan Lyu, et al.
Proceedings of Machine Learning Research|April 30, 2025
Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity LearningJiaqi Wang, Chenxu Zhao, Lingjuan Lyu, et al.
Nature Communications|June 2, 2022
A federated graph neural network framework for privacy-preserving personalizationChuhan Wu, Fangzhao Wu, Lingjuan Lyu, et al.
IEEE Transactions on Neural Networks and Learning Systems|May 16, 2025
SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End DevicesZhengyi Zhong, Weidong Bao, Ji Wang, et al.
IEEE Transactions on Neural Networks and Learning Systems|April 7, 2023
InOR-Net: Incremental 3-D Object Recognition Network for Point Cloud RepresentationJiahua Dong, Yang Cong, Gan Sun, et al.
Patterns (New York, N.Y.)|January 8, 2025
Integration of large language models and federated learningChaochao Chen, Xiaohua Feng, Yuyuan Li, et al.
IEEE Transactions on Neural Networks and Learning Systems|October 29, 2021
Joint Stance and Rumor Detection in Hierarchical Heterogeneous GraphChen Li, Hao Peng, Jianxin Li, et al.
IEEE Transactions on Neural Networks and Learning Systems|November 10, 2022
Privacy and Robustness in Federated Learning: Attacks and DefensesLingjuan Lyu, Han Yu, Xingjun Ma, et al.
Nature Communications|February 21, 2026
Auditing unauthorized training data from AI generated content using information isotopesTao Qi, Jinhua Yin, Dongqi Cai, et al.
Pageof 1