Deniz Gunduz
Imperial College London
596 Papers
2.3K Citations
Deniz Gunduz is an academic researcher from Imperial College London. The author has contributed to research in topics: Computer science & Communication channel. The author has an hindex of 52, co-authored 505 publications. Previous affiliations of Deniz Gunduz include Princeton University & Norwegian University of Science and Technology.
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Papers
FedADC: Accelerated Federated Learning with Drift Control
Emre Ozfatura,Kerem Ozfatura,Deniz Gunduz +2 more
- 12 Jul 2021
TL;DR: FedADC as mentioned in this paper is an accelerated FL algorithm with drift control, which is able to address both problems using a single strategy without any major alteration to the FL framework, or introducing additional computation and communication load.
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Collaborative Semantic Communication for Edge Inference
TL;DR: In this article , two deep learning-based joint source and channel coding (JSCC) schemes were proposed for the task over both additive white Gaussian noise (AWGN) and Rayleigh slow fading channels, with the aim of maximizing the retrieval accuracy under a total bandwidth constraint.
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Semantic-Effectiveness Filtering and Control for Post-5G Wireless Connectivity
TL;DR: In this paper, the authors propose a semantic-effectiveness plane as a core part of future communication architectures, which augments the protocol stack by providing standardized interfaces that enable information filtering and direct control of functionalities at all layers of protocol stack.
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Joint Source-Channel Coding With Time-Varying Channel and Side-Information
TL;DR: The optimal distortion exponent, which quantifies the exponential decay rate of the expected distortion in the high SNR regime, is characterized for Nakagami distributed channel and side information states, and it is shown to be achieved by hybrid digital-analog and joint decoding schemes in certain cases, illustrating the suboptimality of pure digital or analog transmission in general.
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Caching and Coded Delivery over Gaussian Broadcast Channels for Energy Efficiency.
TL;DR: The results in this paper show that proactive caching and coded delivery can provide significant energy savings in wireless networks.
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