Lie He

According to our database1, Lie He authored at least 12 papers between 2018 and 2023.

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Bibliography

2023
Provably Personalized and Robust Federated Learning.
CoRR, 2023

Debiasing Conditional Stochastic Optimization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Byzantine-Robust Decentralized Learning via Self-Centered Clipping.
CoRR, 2022

Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Advances and Open Problems in Federated Learning.
Found. Trends Mach. Learn., 2021

RelaySum for Decentralized Deep Learning on Heterogeneous Data.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning from History for Byzantine Robust Optimization.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Byzantine-Robust Learning on Heterogeneous Datasets via Resampling.
CoRR, 2020

Secure Byzantine-Robust Machine Learning.
CoRR, 2020

2019
Advances and Open Problems in Federated Learning.
CoRR, 2019

2018
COLA: Communication-Efficient Decentralized Linear Learning.
CoRR, 2018

COLA: Decentralized Linear Learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018


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