89 citations · 175 across the 7 of their papers we have counts for
13 papers
Learning Low-Rank Representations for Model Compression
Zezhou Zhu, Yucong Zhou, Zhao Zhong
Vector Quantization (VQ) is an appealing model compression method to obtain a tiny model with less accuracy loss. While methods to obtain better codebooks and codes under fixed clu…
EfficientTrain: Exploring Generalized Curriculum Learning for Training Visual Backbones
Yulin Wang, Yang Yue, Rui Lu +4
The superior performance of modern deep networks usually comes with a costly training procedure. This paper presents a new curriculum learning approach for the efficient training o…
Collaboration of Experts: Achieving 80% Top-1 Accuracy on ImageNet with 100M FLOPs
Yikang Zhang, Zhuo Chen, Zhao Zhong
In this paper, we propose a Collaboration of Experts (CoE) framework to pool together the expertise of multiple networks towards a common aim. Each expert is an individual network…
Learning specialized activation functions with the Piecewise Linear Unit
Yucong Zhou, Zezhou Zhu, Zhao Zhong
The choice of activation functions is crucial for modern deep neural networks. Popular hand-designed activation functions like Rectified Linear Unit(ReLU) and its variants show pro…
FixNorm: Dissecting Weight Decay for Training Deep Neural Networks
Yucong Zhou, Yunxiao Sun, Zhao Zhong
Weight decay is a widely used technique for training Deep Neural Networks(DNN). It greatly affects generalization performance but the underlying mechanisms are not fully understood…
AutoBSS: An Efficient Algorithm for Block Stacking Style Search
Yikang Zhang, Jian Zhang, Zhao Zhong
Neural network architecture design mostly focuses on the new convolutional operator or special topological structure of network block, little attention is drawn to the configuratio…