Deniz Gündüz

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Imperial College London

Professor of Information Processing at Imperial College London

Distributed Learning in Wireless Networks: Recent Progress and Future Challenges

The next-generation of wireless networks will enable many machine learni...
04/05/2021 ∙ by Mingzhe Chen, et al. ∙ 41 ∙ share

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Gradient Coding with Dynamic Clustering for Straggler-Tolerant Distributed Learning

Distributed implementations are crucial in speeding up large scale machi...
03/01/2021 ∙ by Baturalp Buyukates, et al. ∙ 5 ∙ share

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Federated Edge Learning with Misaligned Over-The-Air Computation

Over-the-air computation (OAC) is a promising technique to realize fast ...
02/26/2021 ∙ by Yulin Shao, et al. ∙ 9 ∙ share

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A Reinforcement Learning Approach to Age of Information in Multi-User Networks with HARQ

Scheduling the transmission of time-sensitive information from a source ...
02/19/2021 ∙ by Elif Tuğçe Ceran, et al. ∙ 24 ∙ share

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Active Privacy-utility Trade-off Against a Hypothesis Testing Adversary

We consider a user releasing her data containing some personal informati...
02/16/2021 ∙ by Ecenaz Erdemir, et al. ∙ 10 ∙ share

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Speeding Up Private Distributed Matrix Multiplication via Bivariate Polynomial Codes

We consider the problem of private distributed matrix multiplication und...
02/16/2021 ∙ by Burak Hasircioglu, et al. ∙ 0 ∙ share

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Federated mmWave Beam Selection Utilizing LIDAR Data

Efficient link configuration in millimeter wave (mmWave) communication s...
02/04/2021 ∙ by Mahdi Boloursaz Mashhadi, et al. ∙ 0 ∙ share

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Dopamine: Differentially Private Federated Learning on Medical Data

While rich medical datasets are hosted in hospitals distributed across t...
01/27/2021 ∙ by Mohammad Malekzadeh, et al. ∙ 21 ∙ share

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Time-Correlated Sparsification for Communication-Efficient Federated Learning

Federated learning (FL) enables multiple clients to collaboratively trai...
01/21/2021 ∙ by Emre Ozfatura, et al. ∙ 21 ∙ share

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A Joint Learning and Communication Framework for Multi-Agent Reinforcement Learning over Noisy Channels

We propose a novel formulation of the "effectiveness problem" in communi...
01/02/2021 ∙ by Tze-Yang Tung, et al. ∙ 0 ∙ share

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FedADC: Accelerated Federated Learning with Drift Control

Federated learning (FL) has become de facto framework for collaborative ...
12/16/2020 ∙ by Emre Ozfatura, et al. ∙ 11 ∙ share

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Private Wireless Federated Learning with Anonymous Over-the-Air Computation

We study the problem of differentially private wireless federated learni...
11/17/2020 ∙ by Burak Hasircioglu, et al. ∙ 9 ∙ share

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FedRec: Federated Learning of Universal Receivers over Fading Channels

Wireless communications are often subject to fading conditions. Various ...
11/14/2020 ∙ by Mahdi Boloursaz Mashhadi, et al. ∙ 0 ∙ share

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Distributed Sparse SGD with Majority Voting

Distributed learning, particularly variants of distributed stochastic gr...
11/12/2020 ∙ by Kerem Ozfatura, et al. ∙ 18 ∙ share

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Gradient Coding with Dynamic Clustering for Straggler Mitigation

In distributed synchronous gradient descent (GD) the main performance bo...
11/03/2020 ∙ by Baturalp Buyukates, et al. ∙ 3 ∙ share

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Blind Federated Edge Learning

We study federated edge learning (FEEL), where wireless edge devices, ea...
10/19/2020 ∙ by Mohammad Mohammadi Amiri, et al. ∙ 5 ∙ share

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Communicate to Learn at the Edge

Bringing the success of modern machine learning (ML) techniques to mobil...
09/28/2020 ∙ by Deniz Gündüz, et al. ∙ 0 ∙ share

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Bandwidth-Agile Image Transmission with Deep Joint Source-Channel Coding

We introduce deep learning based communication methods for adaptive-band...
09/26/2020 ∙ by David Burth Kurka, et al. ∙ 0 ∙ share

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On Perfect Obfuscation: Local Information Geometry Analysis

We consider the problem of privacy-preserving data release for a specifi...
09/09/2020 ∙ by Behrooz Razeghi, et al. ∙ 0 ∙ share

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Optimal Scheduling Policy for Minimizing Age of Information with a Relay

We consider IoT sensor network where multiple sensors are connected to c...
09/06/2020 ∙ by Jaeyoung Song, et al. ∙ 0 ∙ share

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Smart Meter Data Privacy

Smart grids (SGs) promise to deliver dramatic improvements compared to t...
09/02/2020 ∙ by Giulio Giaconi, et al. ∙ 0 ∙ share

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Convergence of Federated Learning over a Noisy Downlink

We study federated learning (FL), where power-limited wireless devices u...
08/25/2020 ∙ by Mohammad Mohammadi Amiri, et al. ∙ 4 ∙ share

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Distributed Deep Reinforcement Learning for Functional Split Control in Energy Harvesting Virtualized Small Cells

To meet the growing quest for enhanced network capacity, mobile network ...
08/07/2020 ∙ by Dagnachew Azene Temesgene, et al. ∙ 11 ∙ share

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Wireless Image Retrieval at the Edge

We study the image retrieval problem at the wireless edge, where an edge...
07/21/2020 ∙ by Mikolaj Jankowski, et al. ∙ 0 ∙ share

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Secure Distributed Matrix Computation with Discrete Fourier Transform

We consider the problem of secure distributed matrix computation (SDMC),...
07/08/2020 ∙ by Nitish Mital, et al. ∙ 0 ∙ share

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Coded Distributed Computing with Partial Recovery

Coded computation techniques provide robustness against straggling worke...
07/04/2020 ∙ by Emre Ozfatura, et al. ∙ 0 ∙ share

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Pruning the Pilots: Deep Learning-Based Pilot Design and Channel Estimation for MIMO-OFDM Systems

With the large number of antennas and subcarriers, the overhead due to p...
06/21/2020 ∙ by Mahdi Boloursaz Mashhadi, et al. ∙ 0 ∙ share

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Federated Learning With Quantized Global Model Updates

We study federated learning (FL), which enables mobile devices to utiliz...
06/18/2020 ∙ by Mohammad Mohammadi Amiri, et al. ∙ 0 ∙ share

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Age-Based Coded Computation for Bias Reduction in Distributed Learning

Coded computation can be used to speed up distributed learning in the pr...
06/02/2020 ∙ by Emre Ozfatura, et al. ∙ 0 ∙ share

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Age-of-Information with Information Source Diversity in an Energy Harvesting System

Age of information (AoI) is one of the key performance metrics for Inter...
04/23/2020 ∙ by Elvina Gindullina, et al. ∙ 0 ∙ share

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Straggler-aware Distributed Learning: Communication Computation Latency Trade-off

When gradient descent (GD) is scaled to many parallel workers for large ...
04/10/2020 ∙ by Emre Ozfatura, et al. ∙ 0 ∙ share

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Strong Converse for Testing Against Independence over a Noisy channel

A distributed binary hypothesis testing (HT) problem over a noisy channe...
04/02/2020 ∙ by Sreejith Sreekumar, et al. ∙ 0 ∙ share

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Coded Caching in Multi-server System with Random Topology

Cache-aided content delivery is studied in a multi-server system with P ...
03/09/2020 ∙ by Nitish Mital, et al. ∙ 0 ∙ share

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Distributed Deep Convolutional Compression for Massive MIMO CSI Feedback

Massive multiple-input multiple-output (MIMO) systems require downlink c...
03/07/2020 ∙ by Qianqian Yang, et al. ∙ 11 ∙ share

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Decentralized SGD with Over-the-Air Computation

We study the performance of decentralized stochastic gradient descent (D...
03/06/2020 ∙ by Emre Ozfatura, et al. ∙ 6 ∙ share

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Privacy-Aware Time-Series Data Sharing with Deep Reinforcement Learning

Internet of things (IoT) devices are becoming increasingly popular thank...
03/04/2020 ∙ by Ecenaz Erdemir, et al. ∙ 13 ∙ share

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Deep Joint Transmission-Recognition for Power-Constrained IoT Devices

We propose a joint transmission-recognition scheme for efficient inferen...
03/04/2020 ∙ by Mikolaj Jankowski, et al. ∙ 14 ∙ share

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Deep Learning for Massive MIMO Channel State Acquisition and Feedback

Massive multiple-input multiple-output (MIMO) systems are a main enabler...
02/17/2020 ∙ by Mahdi Boloursaz Mashhadi, et al. ∙ 0 ∙ share

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Update Aware Device Scheduling for Federated Learning at the Wireless Edge

We study federated learning (FL) at the wireless edge, where power-limit...
01/28/2020 ∙ by Mohammad Mohammadi Amiri, et al. ∙ 0 ∙ share

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Bivariate Polynomial Coding for Exploiting Stragglers in Heterogeneous Coded Computing Systems

Polynomial coding has been proposed as a solution to the straggler mitig...
01/20/2020 ∙ by Burak Hasircioglu, et al. ∙ 0 ∙ share

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One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning: Design and Convergence Analysis

Federated edge learning (FEEL) is a popular framework for model training...
01/16/2020 ∙ by Guangxu Zhu, et al. ∙ 0 ∙ share

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Information transmission bounds between moving terminals

In networks of mobile autonomous agents, e.g. for data acquisition, we m...
01/13/2020 ∙ by Omar James Faqir, et al. ∙ 0 ∙ share

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Multi-Antenna Coded Content Delivery with Caching: A Low-Complexity Solution

We study downlink beamforming in a single-cell network with a multi-ante...
01/05/2020 ∙ by Junlin Zhao, et al. ∙ 0 ∙ share

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

We consider wireless transmission of images in the presence of channel o...
11/25/2019 ∙ by David Burth Kurka, et al. ∙ 30 ∙ share

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Average Age-of-Information with a Backup Information Source

Data collected and transmitted by Internet of things (IoT) devices are t...
11/06/2019 ∙ by Elvina Gindullina, et al. ∙ 0 ∙ share

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Energy-Aware Analog Aggregation for Federated Learning with Redundant Data

Federated learning (FL) enables workers to learn a model collaboratively...
11/01/2019 ∙ by Yuxuan Sun, et al. ∙ 0 ∙ share

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Deep Joint Source-Channel Coding for Wireless Image Retrieval

Motivated by surveillance applications with wireless cameras or drones, ...
10/28/2019 ∙ by Mikolaj Jankowski, et al. ∙ 0 ∙ share

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Management and Orchestration of Virtual Network Functions via Deep Reinforcement Learning

Management and orchestration (MANO) of resources by virtual network func...
10/23/2019 ∙ by Joan S. Pujol Roig, et al. ∙ 0 ∙ share

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CNN-based Analog CSI Feedback in FDD MIMO-OFDM Systems

Massive multiple-input multiple-output (MIMO) systems require downlink c...
10/23/2019 ∙ by Mahdi Boloursaz Mashhadi, et al. ∙ 0 ∙ share

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Hierarchical Federated Learning Across Heterogeneous Cellular Networks

We study collaborative machine learning (ML) across wireless devices, ea...
09/05/2019 ∙ by Mehdi Salehi Heydar Abad, et al. ∙ 48 ∙ share

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Deniz Gündüz

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