Towards Efficient and Privacy-Preserving Federated Learning for HMM Training
Author:
Affiliation:
1. Xidian University,State Key Laboratory of Integrated Services Networks,Xi'an,China,710071
2. University of New Brunswick,Faculty of Computer Science,Fredericton,Canada,E3B 5A3
Funder
NSFC
China Postdoctoral Science Foundation
Natural Science Basic Research Plan in Shaanxi Province
Fundamental Research Funds for the Central Universities
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10436708/10436716/10436872.pdf?arnumber=10436872
Reference14 articles.
1. A tutorial on hidden Markov models and selected applications in speech recognition
2. A privacy-preserving and non-interactive federated learning scheme for regression training with gradient descent
3. Achieve Efficient and Privacy-preserving Disease Risk Assessment over Multi-outsourced Vertical Datasets
4. Privacy-Preserving Aggregation for Federated Learning-Based Navigation in Vehicular Fog
5. A Framework for Secure Speech Recognition
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