2 papers
cs.LG2024
Towards Fair, Robust and Efficient Client Contribution Evaluation in Federated Learning
Meiying Zhang, Huan Zhao, Sheldon Ebron +1
The performance of clients in Federated Learning (FL) can vary due to various reasons. Assessing the contributions of each client is crucial for client selection and compensation.…
cs.LG2021
Prototypical Model with Novel Information-theoretic Loss Function for Generalized Zero Shot Learning
Chunlin Ji, Hanchu Shen, Zhan Xiong +3
Generalized zero shot learning (GZSL) is still a technical challenge of deep learning as it has to recognize both source and target classes without data from target classes. To pre…