FedAQT: Accurate Quantized Training with Federated Learning
Author:
Affiliation:
1. University of Maryland,College Park
2. Google LLC,Mountain View,CA,U.S.A
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10445798/10445803/10445824.pdf?arnumber=10445824
Reference25 articles.
1. An Overview of End-to-End Automatic Speech Recognition
2. Attention-based models for speech recognition;Chorowski;Advances in neural information processing systems,2015
3. Speech-Transformer: A No-Recurrence Sequence-to-Sequence Model for Speech Recognition
4. Advances and Open Problems in Federated Learning
5. Conformer: Convolution-augmented Transformer for Speech Recognition
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