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FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning.

M. Tang, X. Ning, Y. Wang, J. Sun, Y. Wang, H. Li, and Y. Chen. CVPR, page 10092-10101. IEEE, (2022)

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Tang Tang

Junhua Tang

Jian Tang

Fei Tang

Xiaofang Tang

Other publications of authors with the same name

Learning Low-rank Deep Neural Networks via Singular Vector Orthogonality Regularization and Singular Value Sparsification.H. Yang, M. Tang, W. Wen, F. Yan, D. Hu, A. Li, H. Li, and Y. Chen. CVPR Workshops, page 2899-2908. Computer Vision Foundation / IEEE, (2020)FADE: Enabling Large-Scale Federated Adversarial Training on Resource-Constrained Edge Devices.M. Tang, J. Zhang, M. Ma, L. DiValentin, A. Ding, A. Hassanzadeh, H. Li, and Y. Chen. CoRR, (2022)FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning.M. Tang, X. Ning, Y. Wang, J. Sun, Y. Wang, H. Li, and Y. Chen. CVPR, page 10092-10101. IEEE, (2022)FedProphet: Memory-Efficient Federated Adversarial Training via Theoretic-Robustness and Low-Inconsistency Cascade Learning.M. Tang, Y. Wang, J. Zhang, L. DiValentin, A. Ding, A. Hass, Y. Chen, and H. Li. CoRR, (2024)Towards collaborative intelligence: routability estimation based on decentralized private data.J. Pan, C. Chang, Z. Xie, A. Li, M. Tang, T. Zhang, J. Hu, and Y. Chen. DAC, page 961-966. ACM, (2022)ModelGuard: Information-Theoretic Defense Against Model Extraction Attacks.M. Tang, A. Dai, L. DiValentin, A. Ding, A. Hass, N. Gong, Y. Chen, and H. Li. USENIX Security Symposium, USENIX Association, (2024)Embracing Privacy, Robustness, and Efficiency with Trustworthy Federated Learning on Edge Devices.M. Tang, J. Sun, H. Li, and Y. Chen. ISVLSI, page 284-289. IEEE, (2024)Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction.J. Zhang, A. Li, M. Tang, J. Sun, X. Chen, F. Zhang, C. Chen, Y. Chen, and H. Li. ICML, volume 202 of Proceedings of Machine Learning Research, page 41354-41381. PMLR, (2023)Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction.J. Zhang, A. Li, M. Tang, J. Sun, X. Chen, F. Zhang, C. Chen, Y. Chen, and H. Li. CoRR, (2022)An Audio Frequency Unfolding Framework for Ultra-Low Sampling Rate Sensors.Z. Gao, M. Tang, A. Li, and Y. Chen. ISQED, page 1-6. IEEE, (2022)

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Disambiguation of "Tang, Minxue"

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FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning.

Please choose a person to relate this publication to

Tang Tang

Junhua Tang

Jian Tang

Fei Tang

Xiaofang Tang

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Tang, Minxue"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning.

Please choose a person to relate this publication to

Tang Tang

Junhua Tang

Jian Tang

Fei Tang

Xiaofang Tang

Other publications of authors with the same name

Disambiguation

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URL
DOI
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Chicago
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FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning.