Hierarchical and tree-like data sets arise in many applications, includi...
Federated clustering is an unsupervised learning problem that arises in ...
Federated learning enables training a global model from data located at ...
Prior solutions for mitigating Byzantine failures in federated learning,...
Federated Learning (FL) is an exciting new paradigm that enables trainin...
Federated learning is a method of training a global model from decentral...
The high demand for computational and storage resources severely impede ...
The high demand for computational and storage resources severely impede ...
We focus on the commonly used synchronous Gradient Descent paradigm for
...
Many distributed graph computing systems have been developed recently fo...