1 code implementation • 27 Feb 2024 • Sunghyeon Woo, Baeseong Park, Byeongwook Kim, Minjung Jo, Sejung Kwon, Dongsuk Jeon, Dongsoo Lee
In this paper, we propose Dropping Backward Propagation (DropBP), a novel approach designed to reduce computational costs while maintaining accuracy.
no code implementations • NeurIPS 2021 • Sunghyeon Woo, Jeongwoo Park, Jiwoo Hong, Dongsuk Jeon
One of the reasons why it is difficult for the brain to perform backpropagation (BP) is the weight transport problem, which argues forward and feedback neurons cannot share the same synaptic weights during learning in biological neural networks.
no code implementations • ICLR 2022 • Sunwoo Lee, Jeongwoo Park, Dongsuk Jeon
In this paper, we propose a method to efficiently find an optimal format without actual training of deep neural networks.
1 code implementation • 5 Feb 2021 • Hyeong-Seok Choi, Sungjin Park, Jie Hwan Lee, Hoon Heo, Dongsuk Jeon, Kyogu Lee
Modern deep learning-based models have seen outstanding performance improvement with speech enhancement tasks.