5 papers · 1 filter
Expected Gain-based Escalation in Vertical Federated Learning
Mohamad Mestoukirdi, Vincent Corlay
Collaborative inference can improve predictive performance by integrating complementary information across agents, but applying collaborative fusion to every sample can incur unnec…
Reliable Vertical Federated Learning in 5G Core Network Architecture
Mohamad Mestoukirdi, Mourad Khanfouci
This work proposes a new algorithm to mitigate model generalization loss in Vertical Federated Learning (VFL) operating under client reliability constraints within 5G Core Networks…
Communication-Efficient Federated Learning via Regularized Sparse Random Networks
Mohamad Mestoukirdi, Omid Esrafilian, David Gesbert +2
This work presents a new method for enhancing communication efficiency in stochastic Federated Learning that trains over-parameterized random networks. In this setting, a binary ma…
User-Centric Federated Learning: Trading off Wireless Resources for Personalization
Mohamad Mestoukirdi, Matteo Zecchin, David Gesbert +1
Statistical heterogeneity across clients in a Federated Learning (FL) system increases the algorithm convergence time and reduces the generalization performance, resulting in a lar…
User-Centric Federated Learning
Mohamad Mestoukirdi, Matteo Zecchin, David Gesbert +2
Data heterogeneity across participating devices poses one of the main challenges in federated learning as it has been shown to greatly hamper its convergence time and generalizatio…