Background Predictive policing and crime analytics with a spatiotemporal focus get
increasing attention among a variety of scientific communities and are already being …

Objectives Gangs are thought to enhance participation in violence. It is expected then that
gang-related violent crimes trigger additional crimes in a contagious manner, above and …

As machine learning is increasingly used to make real-world decisions, recent research
efforts aim to define and ensure fairness in algorithmic decision making. Existing methods …

Police targeting hot spots of crime tends to disproportionately burden minorities via stops
and arrests. This work attempts to reduce disproportionate minority contact by formulating a …

Recent years have witnessed increasing concerns towards unfair decisions made by
machine learning algorithms. To improve fairness in model decisions, various fairness …

The increasing use of algorithms in predictive policing has raised concerns regarding the
potential amplification of societal biases. This study adopts a two-phase approach …

The problem of algorithmic bias in machine learning has gained a lot of attention in recent
years due to its concrete and potentially hazardous implications in society. In much the same …

Background Crime, traffic accidents, terrorist attacks, and other space-time random events
are unevenly distributed in space and time. In the case of crime, hotspot and other proactive …

The application of GIS in the public security industry is generally called “Police Geographic
Information System (PGIS)” in Mainland China. Although China's PGIS play important roles …

Multivariate Hawkes processes have been widely used in many applications such as crime
detection and disaster rescue forecast to model events that exhibit self-exciting properties …