2 citations · 4 across the 3 of their papers we have counts for
4 papers
CHEX: CHannel EXploration for CNN Model Compression
Zejiang Hou, Minghai Qin, Fei Sun +7
Channel pruning has been broadly recognized as an effective technique to reduce the computation and memory cost of deep convolutional neural networks. However, conventional pruning…
Few-shot Learning via Dependency Maximization and Instance Discriminant Analysis
Zejiang Hou, Sun-Yuan Kung
We study the few-shot learning (FSL) problem, where a model learns to recognize new objects with extremely few labeled training data per category. Most of previous FSL approaches r…
A Feature-map Discriminant Perspective for Pruning Deep Neural Networks
Zejiang Hou, Sun-Yuan Kung
Network pruning has become the de facto tool to accelerate deep neural networks for mobile and edge applications. Recently, feature-map discriminant based channel pruning has shown…
Scalable Kernel Learning via the Discriminant Information
Mert Al, Zejiang Hou, Sun-Yuan Kung
Kernel approximation methods create explicit, low-dimensional kernel feature maps to deal with the high computational and memory complexity of standard techniques. This work studie…