Background: Clinical narratives represent the main form of communication within health
care, providing a personalized account of patient history and assessments, and offering rich …

The aim of this study is to provide an overview the state-of-the-art elements of text
classification. For this purpose, we first select and investigate the primary and recent studies …

Self-supervised deep language modeling has shown unprecedented success across natural
language tasks, and has recently been repurposed to biological sequences. However …

Transfer learning aims to learn robust classifiers for the target domain by leveraging
knowledge from a source domain. Since the source and the target domains are usually from …

Lifelong Machine Learning, Second Edition is an introduction to an advanced machine
learning paradigm that continuously learns by accumulating past knowledge that it then …

For the data-driven remaining useful life (RUL) prediction for rolling bearings, the traditional
machine learning-based methods generally provide insufficient feature representation and …

Traditional machine learning algorithms have made great achievements in data-driven fault
diagnosis. However, they assume that all the data must be in the same working condition …

Question generation is an important yet challenging problem in Artificial Intelligence (AI),
which aims to generate natural and relevant questions from various input formats, eg …

This book has been drafted based on my lectures and seminars from recent years for
postgraduate students at Auckland University of Technology (AUT), New Zealand. We have …

The regularization principals [31] lead approximation schemes to deal with various learning
problems, eg, the regularization of the norm in a reproducing kernel Hilbert space for the ill …