11 citations · 12 across the 8 of their papers we have counts for
9 papers
ADROIT6G DAI-driven Open and Programmable Architecture for 6G Networks
Christophoros Christophorou, Iacovos Ioannou, Vasos Vassiliou +10
In the upcoming 6G era, mobile networks must deal with more challenging applications (e.g., holographic telepresence and immersive communication) and meet far more stringent applic…
Communication-Efficient Split Learning Based on Analog Communication and Over the Air Aggregation
Mounssif Krouka, Anis Elgabli, Chaouki ben Issaid +1
Split-learning (SL) has recently gained popularity due to its inherent privacy-preserving capabilities and ability to enable collaborative inference for devices with limited comput…
Energy-Efficient Model Compression and Splitting for Collaborative Inference Over Time-Varying Channels
Mounssif Krouka, Anis Elgabli, Chaouki Ben Issaid +1
Today's intelligent applications can achieve high performance accuracy using machine learning (ML) techniques, such as deep neural networks (DNNs). Traditionally, in a remote DNN i…
Energy-Efficient and Federated Meta-Learning via Projected Stochastic Gradient Ascent
Anis Elgabli, Chaouki Ben Issaid, Amrit S. Bedi +2
In this paper, we propose an energy-efficient federated meta-learning framework. The objective is to enable learning a meta-model that can be fine-tuned to a new task with a few nu…
Efficient Importance Sampling for the Left Tail of Positive Gaussian Quadratic Forms
Chaouki Ben Issaid, Mohamed-Slim Alouini, and Raul Tempone
Estimating the left tail of quadratic forms in Gaussian random vectors is of major practical importance in many applications. In this letter, we propose an efficient importance sam…
Communication Efficient Distributed Learning with Censored, Quantized, and Generalized Group ADMM
Chaouki Ben Issaid, Anis Elgabli, Jihong Park +2
In this paper, we propose a communication-efficiently decentralized machine learning framework that solves a consensus optimization problem defined over a network of inter-connecte…
Harnessing Wireless Channels for Scalable and Privacy-Preserving Federated Learning
Anis Elgabli, Jihong Park, Chaouki Ben Issaid +1
Wireless connectivity is instrumental in enabling scalable federated learning (FL), yet wireless channels bring challenges for model training, in which channel randomness perturbs…
Efficient Estimation of the Left Tail of Bimodal Distributions with Applications to Underwater Optical Communication Systems
Chaouki ben Issaid, Mohamed-Slim Alouini
In this paper, we propose efficient importance sampling estimators to evaluate the outage probability of maximum ratio combining receivers over turbulence-induced fadings in underw…
Eficient Monte Carlo Simulation of the Left Tail of Positive Gaussian Quadratic Forms
Chaouki Ben Issaid, Mohamed-Slim Alouini, Raul Tempone
Estimating the left tail of quadratic forms in Gaussian random vectors is of major practical importance in many applications. In this paper, we propose an efficient and robust impo…