Tyrone Serapio

Spectral Collapse Drives Loss of Plasticity in Deep Continual Learning

We investigate why deep neural networks suffer from loss of plasticity in deep continual learning, failing to learn new tasks without reinitializing parameters. We show that this failure is preceded by Hessian spectral collapse at new-task initialization, where meaningful curvature directions vanish…