732 citations · 1.7k across the 44 of their papers we have counts for
5 papers · 1 filter
Scaff-PD: Communication Efficient Fair and Robust Federated Learning
Yaodong Yu, Sai Praneeth Karimireddy, Yi Ma +1
We present Scaff-PD, a fast and communication-efficient algorithm for distributionally robust federated learning. Our approach improves fairness by optimizing a family of distribut…
Evaluating and Incentivizing Diverse Data Contributions in Collaborative Learning
Baihe Huang, Sai Praneeth Karimireddy, Michael I. Jordan
For a federated learning model to perform well, it is crucial to have a diverse and representative dataset. However, the data contributors may only be concerned with the performanc…
Provably Personalized and Robust Federated Learning
Mariel Werner, Lie He, Michael Jordan +2
Identifying clients with similar objectives and learning a model-per-cluster is an intuitive and interpretable approach to personalization in federated learning. However, doing so…
Federated Conformal Predictors for Distributed Uncertainty Quantification
Charles Lu, Yaodong Yu, Sai Praneeth Karimireddy +2
Conformal prediction is emerging as a popular paradigm for providing rigorous uncertainty quantification in machine learning since it can be easily applied as a post-processing ste…
Online Learning in a Creator Economy
Banghua Zhu, Sai Praneeth Karimireddy, Jiantao Jiao +1
The creator economy has revolutionized the way individuals can profit through online platforms. In this paper, we initiate the study of online learning in the creator economy by mo…