paper (1) 썸네일형 리스트형 [Paper Review] NoProp: Training Neural Networks without Back-propagation or Forward-propagation NoProp: Training Neural Networks without Back-propagation or Forward-propagationThe canonical deep learning approach for learning requires computing a gradient term at each layer by back-propagating the error signal from the output towards each learnable parameter. Given the stacked structure of neural networks, where each layer buildarxiv.org 연구실 세미나 때 발표한 논문이다.논문 내용을 요약하면 propagation을 사용하지 않고 .. 이전 1 다음