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Towards Heterogeneous Clients with Elastic Federated Learning.

, , , , , и . CoRR, (2021)

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Jinfeng Du

Jinfeng Feng

Yi Wang

Weiyong Yi

Yi Ni

 

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On the Adversarial Robustness of Vision Transformers., , , , и . Trans. Mach. Learn. Res., (2022)Improved dynamic regret for non-degeneracy functions., , , , и . CoRR, (2016)Trustworthy AI: From Principles to Practices., , , , , , , и . ACM Comput. Surv., 55 (9): 177:1-177:46 (2023)Inferring Users' Preferences from Crowdsourced Pairwise Comparisons: A Matrix Completion Approach., , , и . HCOMP, стр. 207-215. AAAI, (2013)Hierarchical Personalized Federated Learning for User Modeling., , , , , , , и . WWW, стр. 957-968. ACM / IW3C2, (2021)Defending Against Adversarial Attacks Using Random Forest., , , , , и . CVPR Workshops, стр. 105-114. Computer Vision Foundation / IEEE, (2019)Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning., , , , и . NIPS, стр. 1781-1789. (2012)DTWNet: a Dynamic Time Warping Network., , , , и . NeurIPS, стр. 11636-11646. (2019)FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks., , , , и . ICML, том 202 из Proceedings of Machine Learning Research, стр. 32304-32330. PMLR, (2023)AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks., , , , , , , и . AAAI, стр. 742-749. AAAI Press, (2019)