RNN-based methods have faced challenges in the Long-term Time Series
For...
Recently, Transformer-based models have shown remarkable performance in
...
Self-supervised learning (SSL) speech models such as wav2vec and HuBERT ...
Personalized federated learning, as a variant of federated learning, tra...
Federated learning (FL) is vulnerable to heterogeneously distributed dat...
Both classification and regression tasks are susceptible to the biased
d...
As a key technology in the 5G era, Mobile Edge Computing (MEC) has devel...
With astonishing speed, bandwidth, and scale, Mobile Edge Computing (MEC...
Federated Learning (FL) has shown great potential as a privacy-preservin...
Federated Learning (FL), arising as a novel secure learning paradigm, ha...
The issue of potential privacy leakage during centralized AI's model tra...
Mobile Edge Computing (MEC), which incorporates the Cloud, edge nodes an...
Federated learning (FL) has attracted increasing attention as a promisin...
On-line detection of anomalies in time series is a key technique in vari...