Federated Learning under Heterogeneous and Correlated Client Availability

Author:

Rodio Angelo1,Faticanti Francescomaria1,Marfoq Othmane1,Neglia Giovanni1,Leonardi Emilio2

Affiliation:

1. Inria, Université Côte d’Azur,France

2. Politecnico di Torino,Turin,Italy

Publisher

IEEE

Reference38 articles.

1. Local stochastic approximation: A unified view of federated learning and distributed multi-task reinforcement learning algorithms;doan,2020

2. Measuring Catastrophic Forgetting in Neural Networks

3. Diurnal or Nocturnal? Federated Learning from Periodically Shifting Distributions;zhu;NeurIPS 2021 Workshop on Distribution Shifts Connecting Methods and Applications,2021

4. An empirical investigation of catastrophic forgetting in gradient-based neural networks;goodfellow,2013

5. On Markov chain gradient descent;sun;Advances in neural information processing systems,2018

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