Federated Learning under Distributed Concept Drift

1 code implementation • 1 Jun 2022 • Ellango Jothimurugesan, Kevin Hsieh, Jianyu Wang, Gauri Joshi, Phillip B. Gibbons

Federated Learning (FL) under distributed concept drift is a largely unexplored area.

Clustering Federated Learning

DriftSurf: A Risk-competitive Learning Algorithm under Concept Drift

no code implementations • 13 Mar 2020 • Ashraf Tahmasbi, Ellango Jothimurugesan, Srikanta Tirthapura, Phillip B. Gibbons

The advantage of our approach is that we can use aggressive drift detection in the stable state to achieve a high detection rate, but mitigate the false positive rate of standalone drift detection via a reactive state that reacts quickly to true drifts while eliminating most false positives.

Variance-Reduced Stochastic Gradient Descent on Streaming Data

no code implementations • NeurIPS 2018 • Ellango Jothimurugesan, Ashraf Tahmasbi, Phillip Gibbons, Srikanta Tirthapura

We present an algorithm STRSAGA for efficiently maintaining a machine learning model over data points that arrive over time, quickly updating the model as new training data is observed.