Three types of incremental learning

Gido M. van de Ven, Tinne Tuytelaars, Andreas S. Tolias

Abstract: A challenge for any machine learning system is to continually adapt to new data. While methods to address this issue are developed, their performance is hard to compare. A new framework to facilitate benchmarking divides approaches into three categories, defined by whether models need to adapt to new tasks, domains or classes.