A comprehensive survey of privacy-preserving federated learning: A taxonomy, review, and future directions
The past four years have witnessed the rapid development of federated learning (FL).
However, new privacy concerns have also emerged during the aggregation of the …
However, new privacy concerns have also emerged during the aggregation of the …
A comprehensive survey on transfer learning
Transfer learning aims at improving the performance of target learners on target domains by
transferring the knowledge contained in different but related source domains. In this way, the …
transferring the knowledge contained in different but related source domains. In this way, the …
[HTML][HTML] Pre-trained models: Past, present and future
Large-scale pre-trained models (PTMs) such as BERT and GPT have recently achieved
great success and become a milestone in the field of artificial intelligence (AI). Owing to …
great success and become a milestone in the field of artificial intelligence (AI). Owing to …
Transfer learning promotes 6G wireless communications: Recent advances and future challenges
M Wang, Y Lin, Q Tian, G Si - IEEE Transactions on Reliability, 2021 - ieeexplore.ieee.org
In the coming 6G communications, network densification, high throughput, positioning
accuracy, energy efficiency, and many other key performance indicator requirements are …
accuracy, energy efficiency, and many other key performance indicator requirements are …
Probabilistic model-agnostic meta-learning
Meta-learning for few-shot learning entails acquiring a prior over previous tasks and
experiences, such that new tasks be learned from small amounts of data. However, a critical …
experiences, such that new tasks be learned from small amounts of data. However, a critical …
Recasting gradient-based meta-learning as hierarchical bayes
Meta-learning allows an intelligent agent to leverage prior learning episodes as a basis for
quickly improving performance on a novel task. Bayesian hierarchical modeling provides a …
quickly improving performance on a novel task. Bayesian hierarchical modeling provides a …
A survey of transfer learning for convolutional neural networks
R Ribani, M Marengoni - 2019 32nd SIBGRAPI conference on …, 2019 - ieeexplore.ieee.org
Transfer learning is an emerging topic that may drive the success of machine learning in
research and industry. The lack of data on specific tasks is one of the main reasons to use it …
research and industry. The lack of data on specific tasks is one of the main reasons to use it …
A survey of machine learning for big data processing
There is no doubt that big data are now rapidly expanding in all science and engineering
domains. While the potential of these massive data is undoubtedly significant, fully making …
domains. While the potential of these massive data is undoubtedly significant, fully making …
A survey of transfer learning
K Weiss, TM Khoshgoftaar, DD Wang - Journal of Big data, 2016 - Springer
Abstract Machine learning and data mining techniques have been used in numerous real-
world applications. An assumption of traditional machine learning methodologies is the …
world applications. An assumption of traditional machine learning methodologies is the …