16 citations · 39 across the 10 of their papers we have counts for
3 papers · 1 filter
Mitigating Memory Wall Effects in CNN Engines with On-the-Fly Weights Generation
Stylianos I. Venieris, Javier Fernandez-Marques, Nicholas D. Lane
The unprecedented accuracy of convolutional neural networks (CNNs) across a broad range of AI tasks has led to their widespread deployment in mobile and embedded settings. In a pur…
L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning
Yasar Abbas Ur Rehman, Yan Gao, Pedro Porto Buarque de Gusmão +3
The ubiquity of camera-enabled devices has led to large amounts of unlabeled image data being produced at the edge. The integration of self-supervised learning (SSL) and federated…
Can Fair Federated Learning reduce the need for Personalisation?
Alex Iacob, Pedro P. B. Gusmão, Nicholas D. Lane
Federated Learning (FL) enables training ML models on edge clients without sharing data. However, the federated model's performance on local data varies, disincentivising the parti…