#gradient-free-training News & Analysis

Gradient-Free Training of Spiking Neural Networks via Low-Rank Evolution Strategies

Researchers introduce EGGROLL, a low-rank factorization technique that enables gradient-free training of Spiking Neural Networks (SNNs) using Evolution Strategies, reducing computational overhead by 2.23x while maintaining 79.21% accuracy on N-MNIST. This breakthrough addresses the long-standing challenge of training SNNs on neuromorphic hardware without requiring backpropagation infrastructure.