Evolutionary Data Subset Selection for Class-Incremental Learning on Memory-Constrained Systems
Epifanios Baikas, Danesh Tarapore, David Barrie Thomas · Proceedings of the Genetic and Evolutionary Computation Conference Companion · 2024
Training Machine Learning classifiers on extreme edge devices with non-volatile memory size ≤ 10 MB is challenging because of a) the small number of data examples that can be preserved on-device and b) the dynamic nature of the training dataset caused by the continual collection of new examples. Learning from a stream of data batches, each consisting of examples from a new class, is studied by class-incremental Continual Learning.