activity
20182022
collaborators

5 papers

cs.LG2022

Augmenting Novelty Search with a Surrogate Model to Engineer Meta-Diversity in Ensembles of Classifiers

Rui P. Cardoso, Emma Hart, David Burth Kurka +1

Using Neuroevolution combined with Novelty Search to promote behavioural diversity is capable of constructing high-performing ensembles for classification. However, using gradient…

eess.SP2020

Communicate to Learn at the Edge

Deniz Gunduz, David Burth Kurka, Mikolaj Jankowski +3

Bringing the success of modern machine learning (ML) techniques to mobile devices can enable many new services and businesses, but also poses significant technical and research cha…

cs.IT2019

DeepJSCC-f: Deep Joint Source-Channel Coding of Images with Feedback

David Burth Kurka, Deniz Gündüz

We consider wireless transmission of images in the presence of channel output feedback. From a Shannon theoretic perspective feedback does not improve the asymptotic end-to-end per…

cs.IT2019

Successive Refinement of Images with Deep Joint Source-Channel Coding

David Burth Kurka, Deniz Gunduz

We introduce deep learning based communication methods for successive refinement of images over wireless channels. We present three different strategies for progressive image trans…

cs.IT2018

Deep Joint Source-Channel Coding for Wireless Image Transmission

Eirina Bourtsoulatze, David Burth Kurka, Deniz Gunduz

We propose a joint source and channel coding (JSCC) technique for wireless image transmission that does not rely on explicit codes for either compression or error correction; inste…