We study a new online assignment problem, called the Online Task Assignm...
With the rapid development of deep learning, object detection and tracki...
Latest federated learning (FL) methods started to focus on how to use
un...
Most existing federated learning methods assume that clients have fully
...
The convolutional neural network (CNN) learns the same object in differe...
In the era of Internet of Things (IoT), network-wide anomaly detection i...
In this paper, we propose Hierarchical Federated Learning with Momentum
...
Embedding approaches have become one of the most pervasive techniques fo...
Deep learning techniques have made an increasing impact on the field of
...
Deep learning methods have made significant progress in ship detection i...
There is growing interest in applying distributed machine learning to ed...
Federated learning (FL) is a fast-developing technique that allows multi...
Existing research into online multi-label classification, such as online...
Natural Language Processing (NLP) has been widely used in the semantic
a...
There is an increasing interest in a fast-growing machine learning techn...