10 citations · 12 across the 4 of their papers we have counts for
5 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…
Investigation of Alternative Measures for Mutual Information
Bulut Kuskonmaz, Jaron Skovsted Gundersen, Rafal Wisniewski
Mutual information is a useful definition in information theory to estimate how much information the random variable holds about the random variable . One way to de…
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…
Privacy Preservation in Epidemic Data Collection
Katrine Tjell, Jaron Skovsted Gundersen, Rafael Wisniewski
This work is inspired by the outbreak of COVID-19, and some of the challenges we have observed with gathering data about the disease. To this end, we aim to help collect data about…
Squares of Matrix-product Codes
Ignacio Cascudo, Jaron Skovsted Gundersen, Diego Ruano
The component-wise or Schur product of two linear error correcting codes and over certain finite field is the linear code spanned by all component-wise products of…