With the advent of the Internet of Everything, the proliferation of data has put a huge burden
on data centers and network bandwidth. To ease the pressure on data centers, edge …

Class imbalance is a common issue in the community of machine learning and data mining.
The class-imbalance distribution can make most classical classification algorithms neglect …

Identifying unseen classes with limited labeled data for reference is a challenging task,
which is also known as few-shot learning. Generally, a knowledge-rich model is more robust …

Abstract Few-Shot Event Classification (FSEC) aims at assigning event labels to unlabeled
sentences when limited annotated samples are available. Existing works mainly focus on …

Terminal cancer is not curable and eventually results in death. Breast cancer (BC) is a
prevalent malignancy affecting women. Although there are prognostic indicators, BC …

Least squares regression (LSR) has demonstrated promising performance in various
classification tasks owing to its effectiveness and efficiency. However, there are some …

Background Structural changes in psychiatric systems have altered treatment opportunities
for patients in need of mental healthcare. These changes are possibly associated with an …

Hospital readmissions are regarded as a compounding economic factor for healthcare
systems. In fact, the readmission rate is used in many countries as an indicator of the quality …

Organized retail crime (ORC) is a significant issue for retailers, marketplace platforms, and
consumers. Its prevalence and influence have increased fast in lockstep with the expansion …

This study presents an optimization algorithm, called united equilibrium optimizer (UEO),
which is modified from the equilibrium optimizer (EO). We improved the search structure of …