Semi-supervised federated ASR with online pseudo-labels and server update stabilization for reduced divergence
Read the original at arxiv.org→arXiv:2609.25471v1 Announce Type: new Abstract: Semi-supervised federated learning (SSFL) trains models on clients' unlabeled data using a teacher to generate pseudo-labels, with a small labeled seed dataset on the...
Original headline: "A Practical Recipe for Semi-Supervised Federated ASR: Online Pseudo-Labels with Server Update Stabilization"
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- Sep 23, 04:00 UTC arXiv cs.LG lead source A Practical Recipe for Semi-Supervised Federated ASR: Online Pseudo-Labels with Server Update Stabilization