research
∙
06/14/2023
Provably Personalized and Robust Federated Learning
Clustering clients with similar objectives and learning a model per clus...
share
research
∙
04/20/2023
Debiasing Conditional Stochastic Optimization
In this paper, we study the conditional stochastic optimization (CSO) pr...
research
∙
02/03/2022
Byzantine-Robust Decentralized Learning via Self-Centered Clipping
In this paper, we study the challenging task of Byzantine-robust decentr...
research
∙
10/08/2021
RelaySum for Decentralized Deep Learning on Heterogeneous Data
In decentralized machine learning, workers compute model updates on thei...
research
∙
12/18/2020
Learning from History for Byzantine Robust Optimization
Byzantine robustness has received significant attention recently given i...
research
∙
06/16/2020
Byzantine-Robust Learning on Heterogeneous Datasets via Resampling
In Byzantine robust distributed optimization, a central server wants to ...
research
∙
06/08/2020
Secure Byzantine-Robust Machine Learning
Increasingly machine learning systems are being deployed to edge servers...
research
∙
12/10/2019
Advances and Open Problems in Federated Learning
Federated learning (FL) is a machine learning setting where many clients...
research
∙
08/13/2018
