48 citations · 114 across the 17 of their papers we have counts for
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eess.AS2023★ 1 cited
Importance of Smoothness Induced by Optimizers in FL4ASR: Towards Understanding Federated Learning for End-to-End ASR
Sheikh Shams Azam, Tatiana Likhomanenko, Martin Pelikan +1
In this paper, we start by training End-to-End Automatic Speech Recognition (ASR) models using Federated Learning (FL) and examining the fundamental considerations that can be pivo…
cs.LG2023
Population Expansion for Training Language Models with Private Federated Learning
Tatsuki Koga, Congzheng Song, Martin Pelikan +1
Federated learning (FL) combined with differential privacy (DP) offers machine learning (ML) training with distributed devices and with a formal privacy guarantee. With a large pop…