Publications

2025

  1. ICML
    Leveraging Sparsity for Sample-Efficient Preference Learning: A Theoretical Perspective
    Yunzhen Yao, Lie He, and Michael Gastpar
    CoRR, 2025
    DOI

2024

  1. NeurIPS
    CoBo: Collaborative Learning via Bilevel Optimization
    Diba Hashemi, Lie He†, and Martin Jaggi
    In Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024, 2024

2023

  1. TMLR
    Provably Personalized and Robust Federated Learning
    Mariel A. Werner, Lie He, Michael I. Jordan, and 2 more authors
    Trans. Mach. Learn. Res., 2023
  2. NeurIPS
    Debiasing Conditional Stochastic Optimization
    Lie He and Shiva Prasad Kasiviswanathan
    In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023

2022

  1. ICLR
    Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing
    Sai Praneeth Karimireddy*, Lie He*, and Martin Jaggi
    In The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022, 2022
  2. Byzantine-Robust Decentralized Learning via Self-Centered Clipping
    Lie He, Sai Praneeth Karimireddy, and Martin Jaggi
    CoRR, 2022

2021

  1. FTML
    Advances and Open Problems in Federated Learning
    Peter Kairouz, H. Brendan McMahan, Brendan Avent, and 56 more authors
    Found. Trends Mach. Learn., 2021
    DOI
  2. ICML
    Learning from History for Byzantine Robust Optimization
    Sai Praneeth Karimireddy, Lie He, and Martin Jaggi
    In Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event, 2021
  3. NeurIPS
    RelaySum for Decentralized Deep Learning on Heterogeneous Data
    Thijs Vogels*, Lie He*, Anastasia Koloskova, and 4 more authors
    In Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 2021

2020

  1. NeurIPS-Workshop
    Secure Byzantine-Robust Machine Learning
    Lie He, Sai Praneeth Karimireddy, and Martin Jaggi
    CoRR, 2020

2018

  1. NeurIPS
    COLA: Decentralized Linear Learning
    Lie He*, An Bian*, and Martin Jaggi
    In Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada, 2018