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Differentially Private Federated Learning on Heterogeneous Data.

, , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 10110-10145. PMLR, (2022)

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FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings., , , , , , , , , and 14 other author(s). NeurIPS, (2022)Compression with Exact Error Distribution for Federated Learning., , , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 613-621. PMLR, (2024)Proving Linear Mode Connectivity of Neural Networks via Optimal Transport., , , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 3853-3861. PMLR, (2024)Proving Linear Mode Connectivity of Neural Networks via Optimal Transport., , , and . CoRR, (2023)QLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning., , , , and . CoRR, (2021)Stochastic Approximation Beyond Gradient for Signal Processing and Machine Learning., , , and . IEEE Trans. Signal Process., (2023)On Fundamental Proof Structures in First-Order Optimization., , and . CDC, page 3023-3030. IEEE, (2023)Debiasing Averaged Stochastic Gradient Descent to handle missing values., , , and . NeurIPS, (2020)PEPit: computer-assisted worst-case analyses of first-order optimization methods in Python., , , , , and . Math. Program. Comput., 16 (3): 337-367 (September 2024)Federated-EM with heterogeneity mitigation and variance reduction., , , and . NeurIPS, page 29553-29566. (2021)