Aaron Pache

Mistake gating leads to energy and memory efficient continual learning

This paper introduces mistake-gated learning, a method that reduces synaptic updates by focusing on classification errors, improving energy efficiency and memory usage in continual learning.

Competitive plasticity to reduce the energetic costs of learning

This paper proposes energy-saving plasticity algorithms for neural networks, showing they reduce synaptic updates while maintaining learning performance.