most citedFederated Distillation on Edge Devices: Efficient Client-Side Filtering for Non-IID Data

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Ranked Activation Shift for Post-Hoc Out-of-Distribution Detection

Gianluca Guglielmo, Marc Masana

State-of-the-art post-hoc out-of-distribution detection methods rely on intermediate layer activation editing. However, they exhibit inconsistent performance across datasets and mo…

cs.DC2026

FedADAS: Communication-Efficient Federated Distillation for On-Device Driver Yawn Recognition in Vehicular Networks

Ahmed Mujtaba, Gleb Radchenko, Marc Masana +1

Driver fatigue is a critical safety concern in advanced driver assistance systems. Driver monitoring models trained off-site on static datasets adapt poorly to real-world condition…

cs.CV2026

YawDD+: Frame-level Annotations for Accurate Yawn Prediction

Ahmed Mujtaba, Gleb Radchenko, Marc Masana +1

Driver fatigue remains a leading cause of road accidents, responsible for 24% of crashes. While yawning serves as an early behavioral indicator of fatigue, existing approaches face…

cs.LG20261 cited

Federated Distillation on Edge Devices: Efficient Client-Side Filtering for Non-IID Data

Ahmed Mujtaba, Gleb Radchenko, Radu Prodan +1

Federated distillation has emerged as a promising collaborative machine learning approach, offering enhanced privacy protection and reduced communication compared to traditional fe…

cs.LG2026

Subspace Optimization for Backpropagation-Free Continual Test-Time Adaptation

Damian Sójka, Sebastian Cygert, Marc Masana

We introduce PACE, a backpropagation-free continual test-time adaptation system that directly optimizes the affine parameters of normalization layers. Existing derivative-free appr…