6 citations · 6 across the 3 of their papers we have counts for
3 papers
eess.IV2024
LEARNER: Contrastive Pretraining for Learning Fine-Grained Patient Progression from Coarse Inter-Patient Labels
Jana Armouti, Nikhil Madaan, Rohan Panda +8
Predicting whether a treatment leads to meaningful improvement is a central challenge in personalized medicine, particularly when disease progression manifests as subtle visual cha…
cs.LG2023
Adversarial Robustness Unhardening via Backdoor Attacks in Federated Learning
Taejin Kim, Jiarui Li, Shubhranshu Singh +2
The delicate equilibrium between user privacy and the ability to unleash the potential of distributed data is an important concern. Federated learning, which enables the training o…
cs.LG2022★ 6 cited
Characterizing Internal Evasion Attacks in Federated Learning
Taejin Kim, Shubhranshu Singh, Nikhil Madaan +1
Federated learning allows for clients in a distributed system to jointly train a machine learning model. However, clients' models are vulnerable to attacks during the training and…