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Found 8 papers, 5 papers with code
Federated Learning with Differential Privacy for End-to-End Speech Recognition
($4. 5$, $10^{-9}$)-$\textbf{DP}$) with a 1. 3% (resp.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Importance of Smoothness Induced by Optimizers in FL4ASR: Towards Understanding Federated Learning for End-to-End ASR
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 pivotal in minimizing the performance gap in terms of word error rate between models trained using FL versus their centralized counterpart.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Recycling Model Updates in Federated Learning: Are Gradient Subspaces Low-Rank?
In this paper, we question the rationale behind propagating large numbers of parameters through a distributed system during federated learning.
Federated Learning Beyond the Star: Local D2D Model Consensus with Global Cluster Sampling
Federated learning has emerged as a popular technique for distributing model training across the network edge.
Semi-Decentralized Federated Learning with Cooperative D2D Local Model Aggregations
Federated learning has emerged as a popular technique for distributing machine learning (ML) model training across the wireless edge.
Can we Generalize and Distribute Private Representation Learning?
We study the problem of learning representations that are private yet informative, i. e., provide information about intended "ally" targets while hiding sensitive "adversary" attributes.
Multi-Stage Hybrid Federated Learning over Large-Scale D2D-Enabled Fog Networks
We derive the upper bound of convergence for MH-FL with respect to parameters of the network topology (e. g., the spectral radius) and the learning algorithm (e. g., the number of D2D rounds in different clusters).
Q-Map: Clinical Concept Mining from Clinical Documents
Over the past decade, there has been a steep rise in the data-driven analysis in major areas of medicine, such as clinical decision support system, survival analysis, patient similarity analysis, image analytics etc.
