The current development in deep learning is witnessing an exponential transition into
automation applications. This automation transition can provide a promising framework for …

Class imbalance (CI) in classification problems arises when the number of observations
belonging to one class is lower than the other. Ensemble learning combines multiple models …

Text-to-image generation has recently witnessed remarkable achievements. We introduce a
text-conditional image diffusion model, termed RAPHAEL, to generate highly artistic images …

Federated learning is an emerging distributed machine learning framework for privacy
preservation. However, models trained in federated learning usually have worse …

The recent advances of e-commerce and e-payment systems have sparked an increase in
financial fraud cases such as credit card fraud. It is therefore crucial to implement …

Artificial intelligence (AI) in healthcare plays a pivotal role in combating many fatal diseases,
such as skin, breast, and lung cancer. AI is an advanced form of technology that uses …

Fine-tuning pretrained language models (LMs) without making any architectural changes
has become a norm for learning various language downstream tasks. However, for non …

Fake news is a real problem in today's world, and it has become more extensive and harder
to identify. A major challenge in fake news detection is to detect it in the early phase. Another …

Accurate prediction of ground vibration caused by blasting has always been a significant
issue in the mining industry. Ground vibration caused by blasting is a harmful phenomenon …

Computational drug repurposing aims to identify new indications for existing drugs by
utilizing high-throughput data, often in the form of biomedical knowledge graphs. However …