Author

Baran Can Gül

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#machine learning Preprint Sep 2026

QoS-Aware Federated Learning for Multimodal In-Cabin Interaction in Smart Vehicles

FedQoS is proposed, a novel asynchronous, event-triggered FL framework that decouples local computation from global communication via a two-phase gating mechanism that achieves competitive personalized accuracy with only marginal performance loss compared to FedAvg, while substantially reducing QoS violations.

Baran Can Gül, M. Nakıp, N. Jazdi et al. · 0 citations

Conference Open access Aug 2026

SecureDrive-FL: Joint Differential Privacy and Gradient-Aware Selective Homomorphic Encryption for Federated Driver Monitoring

This work introduces GASHE (Gradient-Aware Selective Homomorphic Encryption), a novel selective encryption strategy that dynamically identifies and encrypts only the gradient components exceeding a DP-calibrated sensitivity threshold, rather than encrypting all parameters uniformly as in static layer-based or full-para...

Baran Can Gül, Hanuma Siddhartha Tunuguntla, Anjana Arvind Naik et al. · IEEE International Conferenc... · 0 citations