Computers are capable of making incredibly accurate predictions on the basis of data they themselves have gathered. In other words, these computers can learn without intervention once they have been pre-programmed by humans. At LIACS, we explore and push the borders of what a revolutionary new generation of algorithms can achieve.
Data contain information that is hard to extract for humans, but can be sieved out by computers. Knowledge Discovery from Data (KDD) concerns the identification of patterns that capture the structure underlying the data. Subgroup discovery, for example, is a topic in pattern mining investigated at LIACS that has been successfully applied to fraud detection and sports analytics.
Every production process is in essence a search for the best combination of a variety of factors, each with their own individual optimum. The art lies in identifying the overall optimum for all of those factors combined. In 2016, our researchers developed a new method for the theory underlying this problem, known as ‘multi-objective optimisation’.