In this paper, to well apply federated learning on biomedical named entity recognition (BioNER), we propose the federated adversarial learning (FAL) method.
The goal is to benefit all platforms from federated learning, via training a global model that predicts with the complete tags set, including all the�...
In this paper, to well apply federated learning on biomedical named entity recognition (BioNER), we propose the federated adversarial learning (FAL) method with�...
To well apply federated learning on biomedical named entity recognition (BioNER), the proposed FAL framework makes use of a modified structured pruning�...
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Read Wonders: To well apply federated learning on biomedical named entity recognition (BioNER), the proposed FAL framework makes use of a modified�...
Apr 25, 2024 � Hanyu Zhao, Sha Yuan, Niantao Xie, Jiahong Leng, Guoqiang Wang: A Federated Adversarial Learning Method for Biomedical Named Entity Recognition.
... Zhao et al. [127] proposed federated adversarial learning (FAL) with biomedical named entity recognition (BioNER). The DP technology was also used to ensure�...
Jul 9, 2023 � Federated learning involves collaborative train- ing with private data from multiple platforms, while not violating data privacy.
This paper explores the progress of NER research from both macro and micro perspectives. It aims to assist researchers in quickly grasping relevant information.
We introduce FLightNER, a collaboratively-trained model in Federated Learning (FL) setting that extends an existing state-of-the-art Named-Entity�...