Search Results for author:
Found 5 papers, 2 papers with code
Toward efficient resource utilization at edge nodes in federated learning
In this paper, we propose and evaluate a FL strategy inspired by transfer learning in order to reduce resource utilization on devices, as well as the load on the server and network in each global training round.
FedBot: Enhancing Privacy in Chatbots with Federated Learning
The POC combines Deep Bidirectional Transformer models and federated learning algorithms to protect customer data privacy during collaborative model training.
FedQAS: Privacy-aware machine reading comprehension with federated learning
In addition, we present the architecture and implementation of the system, as well as provide a reference evaluation based on the SQUAD dataset, to showcase how it overcomes data privacy issues and enables knowledge sharing between alliance members in a Federated learning setting.
Scalable federated machine learning with FEDn
Federated machine learning has great promise to overcome the input privacy challenge in machine learning.
KBot: a Knowledge graph based chatBot for natural language understanding over linked data
With the rapid progress of the semantic web, a huge amount of structured data has become available on the web in the form of knowledge bases (KBs).
