Federated Multi-Task Learning

NeurIPS 2017 Virginia SmithChao-Kai ChiangMaziar SanjabiAmeet Talwalkar

Federated learning poses new statistical and systems challenges in training machine learning models over distributed networks of devices. In this work, we show that multi-task learning is naturally suited to handle the statistical challenges of this setting, and propose a novel systems-aware optimization method, MOCHA, that is robust to practical systems issues... (read more)

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