papers
Publications (13)
cs.LG2023
Byzantine-Robust Decentralized Learning via ClippedGossip
Lie He, Sai Praneeth Karimireddy, Martin Jaggi
cs.LG2026
Non-Asymptotic Analysis of Efficiency in Conformalized Regression
Yunzhen Yao, Lie He, Michael Gastpar
cs.LG2023
Provably Personalized and Robust Federated Learning
Mariel Werner, Lie He, Michael Jordan +2
cs.LG2023
Debiasing Conditional Stochastic Optimization
Lie He, Shiva Prasad Kasiviswanathan
cs.LG2025
Leveraging Sparsity for Sample-Efficient Preference Learning: A Theoretical Perspective
Yunzhen Yao, Lie He, Michael Gastpar
cs.LG2020
Secure Byzantine-Robust Machine Learning
Lie He, Sai Praneeth Karimireddy, Martin Jaggi
cs.AI2026
Joint Consistency: A Unified Test-Time Aggregation Framework via Energy Minimization
Yunzhen Yao, Hongye Wang, Yahong Wang +3
cs.LG2023
Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing
Sai Praneeth Karimireddy, Lie He, Martin Jaggi
cs.LG2024
CoBo: Collaborative Learning via Bilevel Optimization
Diba Hashemi, Lie He, Martin Jaggi
cs.LG2022
RelaySum for Decentralized Deep Learning on Heterogeneous Data
Thijs Vogels, Lie He, Anastasia Koloskova +4
cs.LG2021
Learning from History for Byzantine Robust Optimization
Sai Praneeth Karimireddy, Lie He, Martin Jaggi
cs.LG2021
Advances and Open Problems in Federated Learning
Peter Kairouz, H. Brendan McMahan, Brendan Avent +56
cs.DC2019
COLA: Decentralized Linear Learning
Lie He, An Bian, Martin Jaggi