39 citations · 88 across the 9 of their papers we have counts for
3 papers · 1 filter
Learning from History for Byzantine Robust Optimization
Sai Praneeth Karimireddy, Lie He, Martin Jaggi
Byzantine robustness has received significant attention recently given its importance for distributed and federated learning. In spite of this, we identify severe flaws in existing…
Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing
Sai Praneeth Karimireddy, Lie He, Martin Jaggi
In Byzantine robust distributed or federated learning, a central server wants to train a machine learning model over data distributed across multiple workers. However, a fraction o…
Secure Byzantine-Robust Machine Learning
Lie He, Sai Praneeth Karimireddy, Martin Jaggi
Increasingly machine learning systems are being deployed to edge servers and devices (e.g. mobile phones) and trained in a collaborative manner. Such distributed/federated/decentra…