More information: Wei Guo et al, A comprehensive survey of federated transfer learning: challenges, methods and applications, Frontiers of Computer Science (2024). DOI: 10.1007/s11704-024-40065-x.

3. Federated transfer learning (FTL) uses a pre-trained model on one dataset and fine-tunes it on another, enabling the transfer of insights from one region to another. Here's an outline of the ...

Transfer learning uses models that have been pre-trained on larger datasets. This can save time and resources, as the model doesn't have to be trained from scratch.

In recent decades, computer scientists have been developing increasingly advanced machine learning techniques that can learn ...

Federated learning is also computationally intensive, which may introduce bandwidth, storage space or computing limitations. While the cloud enables on-demand scalability, cybersecurity teams risk ...

For companies like Global Retail Corp., the switch to federated learning isn’t just about technology, it’s about finding a more efficient, secure, and effective way to harness the power of AI.

To provide a comprehensive overview of the latest advancements in the field of Federated Transfer Learning (FTL) and offer valuable insights for researchers, a research team led by Fuzhen Zhuang ...