15 citations · 38 across the 12 of their papers we have counts for
5 papers · 1 filter
MESS+: Energy-Optimal Inferencing in Language Model Zoos with Service Level Guarantees
Ryan Zhang, Herbert Woisetschläger, Shiqiang Wang +1
Open-weight large language model (LLM) zoos allow users to quickly integrate state-of-the-art models into systems. Despite increasing availability, selecting the most appropriate m…
Vertical Federated Learning with Missing Features During Training and Inference
Pedro Valdeira, Shiqiang Wang, Yuejie Chi
Vertical federated learning trains models from feature-partitioned datasets across multiple clients, who collaborate without sharing their local data. Standard approaches assume th…
FADAS: Towards Federated Adaptive Asynchronous Optimization
Yujia Wang, Shiqiang Wang, Songtao Lu +1
Federated learning (FL) has emerged as a widely adopted training paradigm for privacy-preserving machine learning. While the SGD-based FL algorithms have demonstrated considerable…
Federated Learning Priorities Under the European Union Artificial Intelligence Act
Herbert Woisetschläger, Alexander Erben, Bill Marino +4
The age of AI regulation is upon us, with the European Union Artificial Intelligence Act (AI Act) leading the way. Our key inquiry is how this will affect Federated Learning (FL),…
A Survey on Efficient Federated Learning Methods for Foundation Model Training
Herbert Woisetschläger, Alexander Isenko, Shiqiang Wang +2
Federated Learning (FL) has become an established technique to facilitate privacy-preserving collaborative training across a multitude of clients. However, new approaches to FL oft…