federated learning

Communication-efficient federated learning research, and IBM Federated Learning framework.

  • Lorem Ipsum

Open-Source

IBM Federated Learning https://github.com/IBM/federated-learning-lib
PFNM https://github.com/IBM/probabilistic-federated-neural-matching
SPAHM https://github.com/IBM/spahm

IBM Federated Learning

Awards

  • IBM Outstanding Technical Achievement Award
  • IBM A-level accomplishment for contributions toward federated learning

Publications

  1. ICML
    Bayesian Nonparametric Federated Learning of Neural Networks
    Yurochkin, Mikhail, Agarwal, Mayank, Ghosh, Soumya Shubhra, Greenewald, Kristjan H., Hoang, Trong Nghia, and Khazaeni, Yasaman
    In ICML 2019
    HTML
  2. IBM Federated Learning: an Enterprise Framework White Paper V0.1
    Ludwig, Heiko, Baracaldo, Nathalie, Thomas, Gegi, Zhou, Yi, Anwar, Ali, Rajamoni, Shashank, Ong, Yuya Jeremy, Radhakrishnan, Jayaram Kallapalayam, Verma, Ashish, Sinn, Mathieu, Purcell, Mark, Rawat, Ambrish, Minh, Tran Ngoc, Holohan, Naoise, Chakraborty, Supriyo, Whitherspoon, Shalisha, Steuer, Dean, Wynter, Laura, Hassan, Hifaz, Laguna, Sean, Yurochkin, Mikhail, Agarwal, Mayank, Chuba, Ebube, and Abay, Annie
    ArXiv 2020
    HTML
  3. NeurIPS
    Statistical Model Aggregation via Parameter Matching
    Yurochkin, Mikhail, Agarwal, Mayank, Ghosh, Soumya Shubhra, Greenewald, Kristjan H., and Hoang, Trong Nghia
    In NeurIPS 2019
    PDF