Deniz Gündüz

research

∙ 05/08/2022

Transformer-Empowered 6G Intelligent Networks: From Massive MIMO Processing to Semantic Communication

6G wireless networks are foreseen to speed up the convergence of the phy...

Yang Wang, et al. ∙

research

∙ 05/03/2022

Privacy Amplification via Random Participation in Federated Learning

Running a randomized algorithm on a subsampled dataset instead of the en...

Burak Hasircioglu, et al. ∙

research

∙ 04/26/2022

Rate-Constrained Remote Contextual Bandits

We consider a rate-constrained contextual multi-armed bandit (RC-CMAB) p...

Francesco Pase, et al. ∙

research

∙ 03/20/2022

Federated Spatial Reuse Optimization in Next-Generation Decentralized IEEE 802.11 WLANs

As wireless standards evolve, more complex functionalities are introduce...

Francesc Wilhelmi, et al. ∙

research

∙ 02/24/2022

Robust Federated Learning with Connectivity Failures: A Semi-Decentralized Framework with Collaborative Relaying

Intermittent client connectivity is one of the major challenges in centr...

Michal Yemini, et al. ∙

research

∙ 02/17/2022

Time-Correlated Sparsification for Efficient Over-the-Air Model Aggregation in Wireless Federated Learning

Federated edge learning (FEEL) is a promising distributed machine learni...

Yuxuan Sun, et al. ∙

research

∙ 02/16/2022

Efficient Distributed Machine Learning via Combinatorial Multi-Armed Bandits

We consider the distributed stochastic gradient descent problem, where a...

Maximilian Egger, et al. ∙

research

∙ 02/11/2022

Active Privacy-Utility Trade-off Against Inference in Time-Series Data Sharing

Internet of things (IoT) devices, such as smart meters, smart speakers a...

Ecenaz Erdemir, et al. ∙

research

∙ 02/10/2022

Remote Contextual Bandits

We consider a remote contextual multi-armed bandit (CMAB) problem, in wh...

Francesco Pase, et al. ∙

research

∙ 02/07/2022

Over-the-Air Ensemble Inference with Model Privacy

We consider distributed inference at the wireless edge, where multiple c...

Selim F. Yilmaz, et al. ∙

research

∙ 02/01/2022

Learning to Speak on Behalf of a Group: Medium Access Control for Sending a Shared Message

The rapid development of Industrial Internet of Things (IIoT) technologi...

Shaan ul Haque, et al. ∙

research

∙ 12/22/2021

DRF Codes: Deep SNR-Robust Feedback Codes

We present a new deep-neural-network (DNN) based error correction code f...

Mahdi Boloursaz Mashhadi, et al. ∙

research

∙ 12/21/2021

Hierarchical Over-the-Air Federated Edge Learning

Federated learning (FL) over wireless communication channels, specifical...

Ozan Aygün, et al. ∙

research

∙ 12/14/2021

Progressive Feature Transmission for Split Inference at the Wireless Edge

In edge inference, an edge server provides remote-inference services to ...

Qiao Lan, et al. ∙

research

∙ 12/07/2021

Collaborative Learning over Wireless Networks: An Introductory Overview

In this chapter, we will mainly focus on collaborative training across w...

Emre Ozfatura, et al. ∙

research

∙ 11/25/2021

DeepJSCC-Q: Channel Input Constrained Deep Joint Source-Channel Coding

Recent works have shown that the task of wireless transmission of images...

Tze-Yang Tung, et al. ∙

research

∙ 11/25/2021

DeepWiVe: Deep-Learning-Aided Wireless Video Transmission

We present DeepWiVe, the first-ever end-to-end joint source-channel codi...

Tze-Yang Tung, et al. ∙

research

∙ 11/10/2021

Functional Broadcast Repair of Multiple Partial Failures in Wireless Distributed Storage Systems

We consider a distributed storage system with n nodes, where a user can ...

Nitish Mital, et al. ∙

research

∙ 10/08/2021

Privacy-Aware Communication Over the Wiretap Channel with Generative Networks

We study privacy-aware communication over a wiretap channel using end-to...

Ecenaz Erdemir, et al. ∙

research

∙ 09/23/2021

Coded Computation across Shared Heterogeneous Workers with Communication Delay

Distributed computing enables large-scale computation tasks to be proces...

Yuxuan Sun, et al. ∙

research

∙ 09/14/2021

Fast Federated Edge Learning with Overlapped Communication and Computation and Channel-Aware Fair Client Scheduling

We consider federated edge learning (FEEL) over wireless fading channels...

Mehmet Emre Ozfatura, et al. ∙

research

∙ 09/08/2021

Bayesian Over-The-Air Computation

Analog over-the-air computation (OAC) is an efficient solution to a clas...

Yulin Shao, et al. ∙

research

∙ 06/30/2021

Learning to Minimize Age of Information over an Unreliable Channel with Energy Harvesting

The time average expected age of information (AoI) is studied for status...

Elif Tuğçe Ceran, et al. ∙

research

∙ 06/22/2021

Deep Stereo Image Compression with Decoder Side Information using Wyner Common Information

We present a novel deep neural network (DNN) architecture for compressin...

Nitish Mital, et al. ∙

research

∙ 06/18/2021

Less is More: Feature Selection for Adversarial Robustness with Compressive Counter-Adversarial Attacks

A common observation regarding adversarial attacks is that they mostly g...

Emre Ozfatura, et al. ∙

research

∙ 06/14/2021

Bivariate Polynomial Codes for Secure Distributed Matrix Multiplication

We consider the problem of secure distributed matrix multiplication. Cod...

Burak Hasircioglu, et al. ∙

research

∙ 06/05/2021

Variational Leakage: The Role of Information Complexity in Privacy Leakage

We study the role of information complexity in privacy leakage about an ...

Amir Ahooye Atashin, et al. ∙

research

∙ 05/31/2021

Dynamic Scheduling for Over-the-Air Federated Edge Learning with Energy Constraints

Machine learning and wireless communication technologies are jointly fac...

Yuxuan Sun, et al. ∙

research

∙ 05/25/2021

Honest-but-Curious Nets: Sensitive Attributes of Private Inputs can be Secretly Coded into the Entropy of Classifiers' Outputs

It is known that deep neural networks, trained for the classification of...

Mohammad Malekzadeh, et al. ∙

research

∙ 05/24/2021

AirNet: Neural Network Transmission over the Air

State-of-the-art performance for many emerging edge applications is achi...

Mikolaj Jankowski, et al. ∙

research

∙ 05/22/2021

Denoising Noisy Neural Networks: A Bayesian Approach with Compensation

Noisy neural networks (NoisyNNs) refer to the inference and training of ...

Yulin Shao, et al. ∙

research

∙ 05/04/2021

Deep Extended Feedback Codes

A new deep-neural-network (DNN) based error correction encoder architect...

Anahid Robert Safavi, et al. ∙

research

∙ 04/29/2021

A Novel Look at LIDAR-aided Data-driven mmWave Beam Selection

Efficient millimeter wave (mmWave) beam selection in vehicle-to-infrastr...

Matteo Zecchin, et al. ∙

research

∙ 04/05/2021

Distributed Learning in Wireless Networks: Recent Progress and Future Challenges

The next-generation of wireless networks will enable many machine learni...

Mingzhe Chen, et al. ∙

research

∙ 03/01/2021

Gradient Coding with Dynamic Clustering for Straggler-Tolerant Distributed Learning

Distributed implementations are crucial in speeding up large scale machi...

Baturalp Buyukates, et al. ∙

research

∙ 02/26/2021

Federated Edge Learning with Misaligned Over-The-Air Computation

Over-the-air computation (OAC) is a promising technique to realize fast ...

Yulin Shao, et al. ∙

research

∙ 02/19/2021

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

Scheduling the transmission of time-sensitive information from a source ...

Elif Tuğçe Ceran, et al. ∙

research

∙ 02/16/2021

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

We consider a user releasing her data containing some personal informati...

Ecenaz Erdemir, et al. ∙

research

∙ 02/16/2021

Speeding Up Private Distributed Matrix Multiplication via Bivariate Polynomial Codes

We consider the problem of private distributed matrix multiplication und...

Burak Hasircioglu, et al. ∙

research

∙ 02/04/2021

Federated mmWave Beam Selection Utilizing LIDAR Data

Efficient link configuration in millimeter wave (mmWave) communication s...

Mahdi Boloursaz Mashhadi, et al. ∙

research

∙ 01/27/2021

Dopamine: Differentially Private Federated Learning on Medical Data

While rich medical datasets are hosted in hospitals distributed across t...

Mohammad Malekzadeh, et al. ∙

research

∙ 01/21/2021

Time-Correlated Sparsification for Communication-Efficient Federated Learning

Federated learning (FL) enables multiple clients to collaboratively trai...

Emre Ozfatura, et al. ∙

research

∙ 01/02/2021

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...

Tze-Yang Tung, et al. ∙

research

∙ 12/16/2020

FedADC: Accelerated Federated Learning with Drift Control

Federated learning (FL) has become de facto framework for collaborative ...

Emre Ozfatura, et al. ∙

research

∙ 11/17/2020

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

We study the problem of differentially private wireless federated learni...

Burak Hasircioglu, et al. ∙

research

∙ 11/14/2020

FedRec: Federated Learning of Universal Receivers over Fading Channels

Wireless communications are often subject to fading conditions. Various ...

Mahdi Boloursaz Mashhadi, et al. ∙

research

∙ 11/12/2020

Distributed Sparse SGD with Majority Voting

Distributed learning, particularly variants of distributed stochastic gr...

Kerem Ozfatura, et al. ∙

research

∙ 11/03/2020

Gradient Coding with Dynamic Clustering for Straggler Mitigation

In distributed synchronous gradient descent (GD) the main performance bo...

Baturalp Buyukates, et al. ∙

research

∙ 10/19/2020

Blind Federated Edge Learning

We study federated edge learning (FEEL), where wireless edge devices, ea...

Mohammad Mohammadi Amiri, et al. ∙

research

∙ 09/28/2020

Communicate to Learn at the Edge

Bringing the success of modern machine learning (ML) techniques to mobil...

Deniz Gündüz, et al. ∙

Deniz Gündüz

Featured Co-authors