23 citations · 28 across the 5 of their papers we have counts for
5 papers
Towards a privacy-preserving distributed cloud service for preprocessing very large medical images
Yuandou Wang, Neel Kanwal, Kjersti Engan +2
Digitized histopathology glass slides, known as Whole Slide Images (WSIs), are often several gigapixels large and contain sensitive metadata information, which makes distributed pr…
A Comprehensive Study on Dataset Distillation: Performance, Privacy, Robustness and Fairness
Zongxiong Chen, Jiahui Geng, Derui Zhu +5
The aim of dataset distillation is to encode the rich features of an original dataset into a tiny dataset. It is a promising approach to accelerate neural network training and rela…
A Survey on Dataset Distillation: Approaches, Applications and Future Directions
Jiahui Geng, Zongxiong Chen, Yuandou Wang +5
Dataset distillation is attracting more attention in machine learning as training sets continue to grow and the cost of training state-of-the-art models becomes increasingly high.…
An Isolation-Aware Online Virtual Network Embedding via Deep Reinforcement Learning
Ali Gohar, Chunming Rong, Sanghwan Lee
Virtualization technologies are the foundation of modern ICT infrastructure, enabling service providers to create dedicated virtual networks (VNs) that can support a wide range of…
Towards General Deep Leakage in Federated Learning
Jiahui Geng, Yongli Mou, Feifei Li +4
Unlike traditional central training, federated learning (FL) improves the performance of the global model by sharing and aggregating local models rather than local data to protect…