14 citations · 26 across the 5 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
cs.CV2020★ 3 cited
Pruning Filter in Filter
Fanxu Meng, Hao Cheng, Ke Li +4
Pruning has become a very powerful and effective technique to compress and accelerate modern neural networks. Existing pruning methods can be grouped into two categories: filter pr…
cs.LG2020
Filter Grafting for Deep Neural Networks: Reason, Method, and Cultivation
Hao Cheng, Fanxu Meng, Ke Li +4
Filter is the key component in modern convolutional neural networks (CNNs). However, since CNNs are usually over-parameterized, a pre-trained network always contain some invalid (u…
cs.CV2020★ 9 cited
Filter Grafting for Deep Neural Networks
Fanxu Meng, Hao Cheng, Ke Li +4
This paper proposes a new learning paradigm called filter grafting, which aims to improve the representation capability of Deep Neural Networks (DNNs). The motivation is that DNNs…