With the advances in Artificial Intelligence (AI) and the increasing volume of online
educational data, Deep Learning techniques have played a critical role in predicting student …

This paper focuses on the problem of personalized federated learning (FL) with the schema
of contrastive learning (CL), which is to implement collaborative pattern classification by …

The student academic performance prediction is becoming an indispensable service in the
computer supported intelligent education system. But conventional machine learning-based …

Predicting student academic performance is a critical area of education research. Machine
learning (ML) algorithms have gained significant popularity in recent years. The capability to …

This study focuses on specifying local models in federated learning (FL), which allows a
large number of clients to improve their corresponding models by training a shared global …

This paper focuses on the problem of learning discriminative representation for brain
images, which is a critical task toward understanding brain developments. Related studies …

Featured Application As students are usually characterized by more than one learning style,
multi-label classification methods may be applied for the diagnosis of a composite students' …

Acquiring big-size datasets to raise the performance of deep models has become one of the
most critical problems in representation learning (RL) techniques, which is the core potential …

Learning-outcome prediction (LOP) is a longstanding and critical problem in educational
routes. Many studies have contributed to developing effective models while often suffering …

Wind-waves exhibit variations both in shape and steepness, and their asymmetrical nature
is a well-known feature. One of the important characteristics of the sea surface is the front …