23 citations · 25 across the 4 of their papers we have counts for
5 papers
Unconsciously Forget: Mitigating Memorization; Without Knowing What is being Memorized
Er Jin, Yang Zhang, Yongli Mou +4
Recent advances in generative models have demonstrated an exceptional ability to produce highly realistic images. However, previous studies show that generated images often resembl…
LogicAD: Explainable Anomaly Detection via VLM-based Text Feature Extraction
Er Jin, Qihui Feng, Yongli Mou +4
Logical image understanding involves interpreting and reasoning about the relationships and consistency within an image's visual content. This capability is essential in applicatio…
Privacy-Preserving Linkage of Distributed Datasets using the Personal Health Train
Maximilian Jugl, Sascha Welten, Yongli Mou +4
With the generation of personal and medical data at several locations, medical data science faces unique challenges when working on distributed datasets. Growing data protection re…
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…
Distributed Learning for Melanoma Classification using Personal Health Train
Yongli Mou, Sascha Welten, Yeliz Ucer Yediel +2
Skin cancer is the most common cancer type. Usually, patients with suspicion of cancer are treated by doctors without any aided visual inspection. At this point, dermoscopy has bec…