On the convergence of hybrid server-clients collaborative training
Modern distributed machine learning (ML) paradigms, such as federated learning (FL),
utilize data distributed at different clients to train a global model. In such paradigm, local …
utilize data distributed at different clients to train a global model. In such paradigm, local …
Cloud-based Collaborative Agricultural Learning with Flexible Model Size and Adaptive Batch Number
With the rapid growth in the world population, developing agricultural technologies has been
an urgent need. Sensor networks have been widely used to monitor and manage …
an urgent need. Sensor networks have been widely used to monitor and manage …
Federated optimization of smooth loss functions
A Jadbabaie, A Makur, D Shah - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In this work, we study empirical risk minimization (ERM) within a federated learning
framework, where a central server seeks to minimize an ERM objective function using …
framework, where a central server seeks to minimize an ERM objective function using …