14 citations · 23 across the 5 of their papers we have counts for
5 papers
OPQ: Compressing Deep Neural Networks with One-shot Pruning-Quantization
Peng Hu, Xi Peng, Hongyuan Zhu +2
As Deep Neural Networks (DNNs) usually are overparameterized and have millions of weight parameters, it is challenging to deploy these large DNN models on resource-constrained hard…
Contrastive Clustering
Yunfan Li, Peng Hu, Zitao Liu +3
In this paper, we propose a one-stage online clustering method called Contrastive Clustering (CC) which explicitly performs the instance- and cluster-level contrastive learning. To…
Structured Graph Learning for Clustering and Semi-supervised Classification
Zhao Kang, Chong Peng, Qiang Cheng +4
Graphs have become increasingly popular in modeling structures and interactions in a wide variety of problems during the last decade. Graph-based clustering and semi-supervised cla…
You Only Look Yourself: Unsupervised and Untrained Single Image Dehazing Neural Network
Boyun Li, Yuanbiao Gou, Shuhang Gu +3
In this paper, we study two challenging and less-touched problems in single image dehazing, namely, how to make deep learning achieve image dehazing without training on the ground-…
Heterogeneous Representation Learning: A Review
Joey Tianyi Zhou, Xi Peng, Yew-Soon Ong
The real-world data usually exhibits heterogeneous properties such as modalities, views, or resources, which brings some unique challenges wherein the key is Heterogeneous Represen…