Integrated sensing and communications: Toward dual-functional wireless networks for 6G and beyond
As the standardization of 5G solidifies, researchers are speculating what 6G will be. The
integration of sensing functionality is emerging as a key feature of the 6G Radio Access …
integration of sensing functionality is emerging as a key feature of the 6G Radio Access …
Communication-efficient distributed learning: An overview
Distributed learning is envisioned as the bedrock of next-generation intelligent networks,
where intelligent agents, such as mobile devices, robots, and sensors, exchange information …
where intelligent agents, such as mobile devices, robots, and sensors, exchange information …
Model-based deep learning
Signal processing, communications, and control have traditionally relied on classical
statistical modeling techniques. Such model-based methods utilize mathematical …
statistical modeling techniques. Such model-based methods utilize mathematical …
Robust aggregation for federated learning
K Pillutla, SM Kakade… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
We present a novel approach to federated learning that endows its aggregation process with
greater robustness to potential poisoning of local data or model parameters of participating …
greater robustness to potential poisoning of local data or model parameters of participating …
Over-the-air federated learning from heterogeneous data
T Sery, N Shlezinger, K Cohen… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
We focus on over-the-air (OTA) Federated Learning (FL), which has been suggested
recently to reduce the communication overhead of FL due to the repeated transmissions of …
recently to reduce the communication overhead of FL due to the repeated transmissions of …
Task-oriented communications for 6G: Vision, principles, and technologies
Driven by the interplay among artificial intelligence, digital twin, and wireless networks, 6G is
envisaged to go beyond data-centric services to provide intelligent and immersive …
envisaged to go beyond data-centric services to provide intelligent and immersive …
Adversarial attacks on deep neural network: developing robust models against evasion technique
In the fast-paced field of machine learning, it is important to build agile models that can
correctly classify data in the face of enemy attacks. This paper explores the field of …
correctly classify data in the face of enemy attacks. This paper explores the field of …
Scheduling and aggregation design for asynchronous federated learning over wireless networks
Federated Learning (FL) is a collaborative machine learning (ML) framework that combines
on-device training and server-based aggregation to train a common ML model among …
on-device training and server-based aggregation to train a common ML model among …
STAR-RIS integrated nonorthogonal multiple access and over-the-air federated learning: Framework, analysis, and optimization
This article integrates nonorthogonal multiple access (NOMA) and over-the-air federated
learning (AirFL) into a unified framework using one simultaneous transmitting and reflecting …
learning (AirFL) into a unified framework using one simultaneous transmitting and reflecting …
Twenty-five years of sensor array and multichannel signal processing: A review of progress to date and potential research directions
In this article, a general introduction to the area of sensor array and multichannel signal
processing is provided, including associated activities of the IEEE Signal Processing Society …
processing is provided, including associated activities of the IEEE Signal Processing Society …