Mistake gating leads to energy and memory efficient continual learning

Research paper introducing "mistake gating," a technique for improving energy and memory efficiency in continual learning systems. The approach selectively processes errors during incremental learning to reduce computational overhead. Addresses practical constraints for deploying continual learning on resource-constrained devices.