Real-world data streams pose a unique challenge to the implementation of machine
learning (ML) models and data analysis. A notable problem that has been introduced by the …

We are concerned with the issue of detecting model changes in probability distributions. We
specifically consider the strategies based on the minimum description length (MDL) …

We are concerned with the issue of detecting changes and their signs from a data stream.
For example, when given time series of COVID-19 cases in a region, we may raise early …

The detection of network changes over time is based on identifying deviations of the network
structure. The challenge mainly lies in designing a good summary or descriptor of the …

This paper addresses the issue of how we can detect changes of changes, which we call
metachanges, in data streams. A metachange refers to a change in patterns of when and …

When considering a data set it is often unknown how complex it is, and hence it is difficult to
assess how rich a model for the data should be. Often these choices are swept under the …

Distributed streaming applications, ie, applications that process massive streams of data in a
distributed fashion, are becoming increasingly popular to tame the velocity and the volume …

In this chapter, we show an application of the MDL principle to change detection. It is one of
most practically important issues in data science, where the MDL principle plays a key role …

Exponential population growth and urbanisation pose potential challenges to mobility,
governance, well-being, the environment, and the safety of modern cities. This demands …

This paper addresses the issue of how we can detect changes of changes, which we call
metachanges, in data streams. A metachange refers to a change in patterns of when and …