Continual Learning for Smart City: A Survey

Understand

With the digitization of modern cities, large data volumes and powerful computational resources facilitate the rapid update of intelligent models deployed in smart cities.

• Continual learning (CL) is a novel machine learning paradigm that constantly updates models to adapt to changing environments, where the learning tasks, data, and distributions can vary over time.
• Our survey provides a comprehensive review of continual learning methods that are widely used in smart city development.
• The content consists of three parts: 1) Methodology-wise.