Time series remains one of the most challenging modalities in machine
le...
Federated learning (FL) has emerged as a new paradigm for privacy-preser...
Domain generalization (DG) aims to learn a generalizable model from mult...
Time series classification is an important problem in real world. Due to...
The distribution shifts between training and test data typically undermi...
Deep learning has achieved great success in the past few years. However,...
Human activity recognition requires the efforts to build a generalizable...
Federated learning has attracted increasing attention to building models...
It is expensive and time-consuming to collect sufficient labeled data to...
There is a growing interest in applying machine learning techniques for
...
The success of machine learning applications often needs a large quantit...