7 citations · 11 across the 4 of their papers we have counts for
3 papers
cs.LG2022
Training Large-Vocabulary Neural Language Models by Private Federated Learning for Resource-Constrained Devices
Mingbin Xu, Congzheng Song, Ye Tian +10
Federated Learning (FL) is a technique to train models using data distributed across devices. Differential Privacy (DP) provides a formal privacy guarantee for sensitive data. Our…
cs.LG2022★ 4 cited
FLAIR: Federated Learning Annotated Image Repository
Congzheng Song, Filip Granqvist, Kunal Talwar
Cross-device federated learning is an emerging machine learning (ML) paradigm where a large population of devices collectively train an ML model while the data remains on the devic…
cs.NE2016★ 7 cited
Learning Genomic Representations to Predict Clinical Outcomes in Cancer
Safoora Yousefi, Congzheng Song, Nelson Nauata +1
Genomics are rapidly transforming medical practice and basic biomedical research, providing insights into disease mechanisms and improving therapeutic strategies, particularly in c…