Supervisor: Dr Tim Hospedales
Traditional supervised machine learning attempts to solve any posed problem from scratch. Lifelong machine learning aims to provide the more humanlike ability to run for an extended period of time, addressing many diverse problems, and eventually learning general knowledge / skills that can be re-used to help improve performance at all tasks, and especially improve the efficiency of acquiring new skills. This project will focus on online algorithms for life-long learning. How can knowledge be restructured, re-used and synergistically combined when dealing with a realistic stream of tasks. Possible application areas include computer vision/multimedia, or robotics.