Recent works on over-parameterized neural networks have shown that the
s...
In classical federated learning, the clients contribute to the overall
t...
Negative sampling schemes enable efficient training given a large number...
Federated Learning (FL) is a distributed learning paradigm which scales
...
Federated learning is a distributed machine learning paradigm in which a...
We study distributed optimization algorithms for minimizing the average ...
In the learning to learn (L2L) framework, we cast the design of optimiza...