activity
20192021
most citedMulti-Objective Pruning for CNNs Using Genetic Algorithm

4 citations · 6 across the 4 of their papers we have counts for

collaborators

5 papers

cs.NI2021

A Channel-Aware Routing Protocol With Nearest Neighbor Regression For Underwater Sensor Networks

Boyu Diao, Chao Li, Qi Wang +2

The underwater acoustic channel is one of the most challenging communication channels. Due to periodical tidal and daily climatic variation, underwater noise is periodically fluctu…

cs.DC20211 cited

A Distributed SGD Algorithm with Global Sketching for Deep Learning Training Acceleration

LingFei Dai, Boyu Diao, Chao Li +1

Distributed training is an effective way to accelerate the training process of large-scale deep learning models. However, the parameter exchange and synchronization of distributed…

cs.CV20201 cited

Channel Pruning via Multi-Criteria based on Weight Dependency

Yangchun Yan, Rongzuo Guo, Chao Li +2

Channel pruning has demonstrated its effectiveness in compressing ConvNets. In many related arts, the importance of an output feature map is only determined by its associated filte…

cs.CV2019

Gated Convolutional Networks with Hybrid Connectivity for Image Classification

Chuanguang Yang, Zhulin An, Hui Zhu +5

We propose a simple yet effective method to reduce the redundancy of DenseNet by substantially decreasing the number of stacked modules by replacing the original bottleneck by our…

cs.NE20194 cited

Multi-Objective Pruning for CNNs Using Genetic Algorithm

Chuanguang Yang, Zhulin An, Chao Li +2

In this work, we propose a heuristic genetic algorithm (GA) for pruning convolutional neural networks (CNNs) according to the multi-objective trade-off among error, computation and…