3 citations · 3 across the 6 of their papers we have counts for
5 papers · 1 filter
Communication-Efficient and Interoperable Distributed Learning
Mounssif Krouka, Mehdi Bennis
Collaborative learning across heterogeneous model architectures presents significant challenges in ensuring interoperability and preserving privacy. We propose a communication-effi…
Distributionally Robust Federated Learning with Client Drift Minimization
Mounssif Krouka, Chaouki Ben Issaid, Mehdi Bennis
Federated learning (FL) faces critical challenges, particularly in heterogeneous environments where non-independent and identically distributed data across clients can lead to unfa…
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…
Cross Layer Optimization and Distributed Reinforcement Learning for Wireless 360° Video Streaming
Anis Elgabli, Mohammed S. Elbamby, Cristina Perfecto +3
Wirelessly streaming high quality 360 degree videos is still a challenging problem. When there are many users watching different 360 degree videos and competing for the computing a…