COLA: Decentralized Linear Learning. - Lie He; An Bian; Martin Jaggi (NeurIPS, 2018)

COLA: Communication-Efficient Decentralized Linear Learning. - Lie He; An Bian; Martin Jaggi (CoRR, 2018)

Advances and Open Problems in Federated Learning. - Peter Kairouz; H. Brendan McMahan; Brendan Avent; Aurélien Bellet; Mehdi Bennis; Arjun Nitin Bhagoji; Kallista A. Bonawitz; Zachary Charles; Graham Cormode; Rachel Cummings; Rafael G. L. D'Oliveira; Salim El Rouayheb; et al. (CoRR, 2019)

Secure Byzantine-Robust Machine Learning. - Lie He; Sai Praneeth Karimireddy; Martin Jaggi (CoRR, 2020)

Byzantine-Robust Learning on Heterogeneous Datasets via Resampling. - Lie He; Sai Praneeth Karimireddy; Martin Jaggi (CoRR, 2020)

Learning from History for Byzantine Robust Optimization. - Sai Praneeth Karimireddy; Lie He; Martin Jaggi (ICML, 2021)

RelaySum for Decentralized Deep Learning on Heterogeneous Data. - Thijs Vogels; Lie He; Anastasia Koloskova; Sai Praneeth Karimireddy; Tao Lin 004; Sebastian U. Stich; Martin Jaggi (NeurIPS, 2021)

Advances and Open Problems in Federated Learning. - Peter Kairouz; H. Brendan McMahan; Brendan Avent; Aurélien Bellet; Mehdi Bennis; Arjun Nitin Bhagoji; Kallista A. Bonawitz; Zachary Charles; Graham Cormode; Rachel Cummings; Rafael G. L. D'Oliveira; Hubert Eichner; et al. (Found. Trends Mach. Learn., 2021)

Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing. - Sai Praneeth Karimireddy; Lie He; Martin Jaggi (ICLR, 2022)

Byzantine-Robust Decentralized Learning via Self-Centered Clipping. - Lie He; Sai Praneeth Karimireddy; Martin Jaggi (CoRR, 2022)

Debiasing Conditional Stochastic Optimization. - Lie He; Shiva Prasad Kasiviswanathan (NeurIPS, 2023)

Provably Personalized and Robust Federated Learning. - Mariel A. Werner; Lie He; Michael I. Jordan; Martin Jaggi; Sai Praneeth Karimireddy (Trans. Mach. Learn. Res., 2023)

CoBo: Collaborative Learning via Bilevel Optimization. - Diba Hashemi; Lie He; Martin Jaggi (NeurIPS, 2024)

Leveraging Sparsity for Sample-Efficient Preference Learning: A Theoretical Perspective. - Yunzhen Yao; Lie He; Michael Gastpar (CoRR, 2025)