<ul><li>Continual learning (CL) is a technique for maintaining a small forgetting loss on previously-learned tasks in an online learning setup.</li><li>Existing work focuses on reducing forgetting loss under a given task sequence, but fails to address the issue of huge forgetting loss on prior distinct tasks if similar tasks continuously appear.</li><li>In IoT networks, where an autonomous vehicle samples data and learns different tasks, the order of task patterns can be altered at an increased travelling cost.</li><li>Researchers have formulated a new optimization problem to study how to opportunistically route the testing object and alter the task sequence in CL, achieving close-to-optimum performance.</li></ul>

Algorithm Design for Continual Learning in IoT Networks

Discover more