10 citations · 15 across the 9 of their papers we have counts for
13 papers
Privacy-Preserving Distributed Expectation Maximization for Gaussian Mixture Model using Subspace Perturbation
Qiongxiu Li, Jaron Skovsted Gundersen, Katrine Tjell +2
Privacy has become a major concern in machine learning. In fact, the federated learning is motivated by the privacy concern as it does not allow to transmit the private data but on…
A deep representation learning speech enhancement method using -VAE
Yang Xiang, Jesper Lisby Højvang, Morten Højfeldt Rasmussen +1
In previous work, we proposed a variational autoencoder-based (VAE) Bayesian permutation training speech enhancement (SE) method (PVAE) which indicated that the SE performance of t…
A Bayesian Permutation training deep representation learning method for speech enhancement with variational autoencoder
Yang Xiang, Jesper Lisby Højvang, Morten Højfeldt Rasmussen +1
Recently, variational autoencoder (VAE), a deep representation learning (DRL) model, has been used to perform speech enhancement (SE). However, to the best of our knowledge, curren…
Communication efficient privacy-preserving distributed optimization using adaptive differential quantization
Qiongxiu Li, Richard Heusdens, Mads Græsbøll Christensen
Privacy issues and communication cost are both major concerns in distributed optimization. There is often a trade-off between them because the encryption methods required for priva…
Speech Decomposition Based on a Hybrid Speech Model and Optimal Segmentation
Alfredo Esquivel Jaramillo, Jesper Kjær Nielsen, Mads Græsbøll Christensen
In a hybrid speech model, both voiced and unvoiced components can coexist in a segment. Often, the voiced speech is regarded as the deterministic component, and the unvoiced speech…
Privacy-Preserving Distributed Processing: Metrics, Bounds, and Algorithms
Qiongxiu Li, Jaron Skovsted Gundersen, Richard Heusdens +1
Privacy-preserving distributed processing has recently attracted considerable attention. It aims to design solutions for conducting signal processing tasks over networks in a decen…