90 citations · 326 across the 16 of their papers we have counts for
5 papers · 1 filter
Robust Generalization of Graph Neural Networks for Carrier Scheduling
Daniel F. Perez-Ramirez, Carlos Pérez-Penichet, Nicolas Tsiftes +3
Battery-free sensor tags are devices that leverage backscatter techniques to communicate with standard IoT devices, thereby augmenting a network's sensing capabilities in a scalabl…
An Experimental Study of Byzantine-Robust Aggregation Schemes in Federated Learning
Shenghui Li, Edith C. -H. Ngai, Thiemo Voigt
Byzantine-robust federated learning aims at mitigating Byzantine failures during the federated training process, where malicious participants may upload arbitrary local updates to…
On-device Training: A First Overview on Existing Systems
Shuai Zhu, Thiemo Voigt, JeongGil Ko +1
The recent breakthroughs in machine learning (ML) and deep learning (DL) have catalyzed the design and development of various intelligent systems over wide application domains. Whi…
DeepGANTT: A Scalable Deep Learning Scheduler for Backscatter Networks
Daniel F. Perez-Ramirez, Carlos Pérez-Penichet, Nicolas Tsiftes +3
Novel backscatter communication techniques enable battery-free sensor tags to interoperate with unmodified standard IoT devices, extending a sensor network's capabilities in a scal…
Auto-weighted Robust Federated Learning with Corrupted Data Sources
Shenghui Li, Edith Ngai, Fanghua Ye +1
Federated learning provides a communication-efficient and privacy-preserving training process by enabling learning statistical models with massive participants while keeping their…