2025
BP-Modified Local Loss for Efficient Training of Deep Neural Networks
ICLR 2025poster
The training of large models is memory-constrained, one direction to relieve this is training using local loss, like GIM, LoCo, and Forward-Forward algorithms. However, the local loss methods often face the issue of slow or non-convergence. In this paper, we propose a novel BP-modified l…