With advanced digitalisation, we can observe a massive increase of user-generated content
on the web that provides opinions of people on different subjects. Sentiment analysis is the …

Multi-view learning is an emerging direction in machine learning which considers learning
with multiple views to improve the generalization performance. Multi-view learning is also …

Semi-supervised learning is the branch of machine learning concerned with using labelled
as well as unlabelled data to perform certain learning tasks. Conceptually situated between …

State-of-the-art deep learning models are often trained with a large amount of costly labeled
training data. However, requiring exhaustive manual annotations may degrade the model's …

We propose TabTransformer, a novel deep tabular data modeling architecture for
supervised and semi-supervised learning. The TabTransformer is built upon self-attention …

Self-training methods have gained significant attention in recent years due to their
effectiveness in leveraging small labeled datasets and large unlabeled observations for …

Deep learning has led to tremendous progress in the field of medical artificial intelligence.
However, training deep-learning models usually require large amounts of annotated data …

Recent advances in semi-supervised semantic segmentation have been heavily reliant on
pseudo labeling to compensate for limited labeled data, disregarding the valuable relational …

The purpose of document classification is to assign the most appropriate label to a specified
document. The main challenges in document classification are insufficient label information …

Android has become the target of attackers because of its popularity. The detection of
Android mobile malware has become increasingly important due to its significant threat …