The distribution of the health data monitored from mechanical system in the industries is
class imbalanced mainly. The amount of monitoring data for the normal condition is far more …

When trained effectively, the Variational Autoencoder (VAE) can be both a powerful
generative model and an effective representation learning framework for natural language …

Data-driven fault diagnosis techniques are frequently applied to ensure the reliability and
safety of industrial systems. However, as a common challenge, the class-imbalance problem …

The recent spread of Deep Learning-based solutions for Artificial Intelligence and the
development of Large Language Models has pushed forwards significantly the Natural …

The core principle of Variational Inference (VI) is to convert the statistical inference problem
of computing complex posterior probability densities into a tractable optimization problem …

The goal of cross-domain sentiment classification is to utilise useful information in the source
domain to help classify sentiment polarity in the target domain, which has a large number of …

The past several years have witnessed Variational Auto-Encoder's superiority in various text
generation tasks. However, due to the sequential nature of the text, auto-regressive …

The recent development of recommender systems has a focus on collaborative ranking,
which provides users with a sorted list rather than rating prediction. The sorted item lists can …

Multi-view or even multi-modal data is appealing yet challenging for real-world applications.
Detecting anomalies in multi-view data is a prominent recent research topic. However, most …

A job description shows the responsibilities of the job position and the skill requirements for
the job. An effective job description will help employers to identify the right talents for the job …