Abstract Machine learning and optimisation are two growing fields of artificial intelligence
with an enormous number of computer science applications. The techniques in the former …

Deep neural networks have been proven powerful at processing perceptual data, such as
images and audio. However for tabular data, tree-based models are more popular. A nice …

Packet classification is a fundamental problem in computer networking. This problem
exposes a hard tradeoff between the computation and state complexity, which makes it …

The tree-based model is widely applied in classification and regression problems because
of its interpretability. Self-adaptive forest models are proposed for adapting to dynamic …

In this paper we propose a method to build a neural network that is similar to an ensemble of
decision trees. We first illustrate how to convert a learned ensemble of decision trees to a …

Identity recognition plays an important role in ensuring security in our daily life. Biometric-
based (especially activity-based) approaches are favored due to their fidelity, universality …

Focusing on Random Forests, we propose a multi-armed contextual bandit recommendation
framework for feature-based selection of a single shallow tree of the learned ensemble. The …

There is an increasing consensus about the effectiveness of user-centred approaches in the
explainable artificial intelligence (XAI) field. Indeed, the number and complexity of …

Curling, also known as" chess on ice", is a popular worldwide sport, which not only tests the
physical and mental strength of the participants but also showcases the beauty of movement …

Out-of-distribution generalization is becoming a hot research topic in both academia and
industry. This tutorial is to disseminate and promote the recent research achievements on …