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Differentially Private Federated Learning on Heterogeneous Data.

, , и . AISTATS, том 151 из Proceedings of Machine Learning Research, стр. 10110-10145. PMLR, (2022)

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Aurélien Bellet

Aurélien Carlier

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Learning Fair Scoring Functions: Fairness Definitions, Algorithms and Generalization Bounds for Bipartite Ranking., , и . CoRR, (2020)Federated Multi-Task Learning under a Mixture of Distributions., , , , и . NeurIPS, стр. 15434-15447. (2021)Evaluating Voice Conversion-Based Privacy Protection against Informed Attackers., , , , , и . ICASSP, стр. 2802-2806. IEEE, (2020)Privacy Amplification by Decentralization., и . CoRR, (2020)D-Cliques: Compensating for Data Heterogeneity with Topology in Decentralized Federated Learning., , и . SRDS, стр. 1-11. IEEE, (2022)Fair Without Leveling Down: A New Intersectional Fairness Definition., , , и . EMNLP, стр. 9018-9032. Association for Computational Linguistics, (2023)metric-learn: Metric Learning Algorithms in Python., , , , и . J. Mach. Learn. Res., (2020)Collaborative Algorithms for Online Personalized Mean Estimation., , , и . CoRR, (2022)Fair NLP Models with Differentially Private Text Encoders., , , и . EMNLP (Findings), стр. 6913-6930. Association for Computational Linguistics, (2022)Differential Privacy has Bounded Impact on Fairness in Classification., , , и . ICML, том 202 из Proceedings of Machine Learning Research, стр. 23681-23705. PMLR, (2023)