Communication-efficient on-device machine learning: Federated distillation and augmentation under non-iid private data

E Jeong, S Oh, H Kim, J Park, M Bennis… - arXiv preprint arXiv …, 2018 - arxiv.org
On-device machine learning (ML) enables the training process to exploit a massive amount
of user-generated private data samples. To enjoy this benefit, inter-device communication …
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Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data

E Jeong, S Oh, H Kim, J Park, M Bennis… - arXiv e …, 2018 - ui.adsabs.harvard.edu
On-device machine learning (ML) enables the training process to exploit a massive amount
of user-generated private data samples. To enjoy this benefit, inter-device communication …
[PDF] researchgate.net

[PDF][PDF] Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data

E Jeong, S Oh, H Kim, SL Kim, J Park… - arXiv preprint arXiv …, 2018 - researchgate.net
On-device machine learning (ML) enables the training process to exploit a massive amount
of user-generated private data samples. To enjoy this benefit, inter-device communication …