Barriers for Learning in an Evolving World: Mathematical Understanding of Loss of Plasticity

Researchers have identified the mathematical mechanisms behind 'loss of plasticity' (LoP), explaining why deep learning models struggle to continue learning in changing environments. The study reveals that properties promoting generalization in static settings actually hinder continual learning by creating parameter space traps.