Defang Chen

According to our database, Defang Chen authored at least 30 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2024

Online adversarial knowledge distillation for graph neural networks.

Can Wang, Zhe Wang, Defang Chen, Sheng Zhou, Yan Feng, Chun Chen

Expert Syst. Appl., March, 2024

Knowledge Translation: A New Pathway for Model Compression.

Wujie Sun, Defang Chen, Jiawei Chen, Yan Feng, Chun Chen, Can Wang

CoRR, 2024

2023

Collaborative Semantic Aggregation and Calibration for Federated Domain Generalization.

Junkun Yuan, Xu Ma, Defang Chen, Fei Wu, Lanfen Lin, Kun Kuang

IEEE Trans. Knowl. Data Eng., December, 2023

Finalizing your reference list with machine learning.

Jian-Ping Mei, Defang Chen, Jing Fan, Lianghuai Yang

J. Ambient Intell. Humaniz. Comput., November, 2023

Online cross-layer knowledge distillation on graph neural networks with deep supervision.

Jiongyu Guo, Defang Chen, Can Wang

Neural Comput. Appl., October, 2023

SemCKD: Semantic Calibration for Cross-Layer Knowledge Distillation.

Can Wang, Defang Chen, Jian-Ping Mei, Yuan Zhang, Yan Feng, Chun Chen

IEEE Trans. Knowl. Data Eng., June, 2023

Domain-Specific Bias Filtering for Single Labeled Domain Generalization.

Junkun Yuan, Xu Ma, Defang Chen, Kun Kuang, Fei Wu, Lanfen Lin

Int. J. Comput. Vis., 2023

Fast ODE-based Sampling for Diffusion Models in Around 5 Steps.

Zhenyu Zhou, Defang Chen, Can Wang, Chun Chen

CoRR, 2023

A Geometric Perspective on Diffusion Models.

Defang Chen, Zhenyu Zhou, Jian-Ping Mei, Chunhua Shen, Chun Chen, Can Wang

CoRR, 2023

Knowledge Distillation with Deep Supervision.

Shiya Luo, Defang Chen, Can Wang

Proceedings of the International Joint Conference on Neural Networks, 2023

Adaptive Multi-Teacher Knowledge Distillation with Meta-Learning.

Hailin Zhang, Defang Chen, Can Wang

Proceedings of the IEEE International Conference on Multimedia and Expo, 2023

Accelerating Diffusion Sampling with Classifier-based Feature Distillation.

Wujie Sun, Defang Chen, Can Wang, Deshi Ye, Yan Feng, Chun Chen

Proceedings of the IEEE International Conference on Multimedia and Expo, 2023

Holistic Weighted Distillation for Semantic Segmentation.

Wujie Sun, Defang Chen, Can Wang, Deshi Ye, Yan Feng, Chun Chen

Proceedings of the IEEE International Conference on Multimedia and Expo, 2023

Customizing Synthetic Data for Data-Free Student Learning.

Shiya Luo, Defang Chen, Can Wang

Proceedings of the IEEE International Conference on Multimedia and Expo, 2023

2022

JointE: Jointly utilizing 1D and 2D convolution for knowledge graph embedding.

Zhehui Zhou, Can Wang, Yan Feng, Defang Chen

Knowl. Based Syst., 2022

Improving Knowledge Graph Embedding via Iterative Self-Semantic Knowledge Distillation.

Zhehui Zhou, Defang Chen, Can Wang, Yan Feng, Chun Chen

CoRR, 2022

Deeply-Supervised Knowledge Distillation.

Shiya Luo, Defang Chen, Can Wang

CoRR, 2022

Collaborative Knowledge Distillation for Heterogeneous Information Network Embedding.

Can Wang, Sheng Zhou, Kang Yu, Defang Chen, Bolang Li, Yan Feng, Chun Chen

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Label-Efficient Domain Generalization via Collaborative Exploration and Generalization.

Junkun Yuan, Xu Ma, Defang Chen, Kun Kuang, Fei Wu, Lanfen Lin

Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Alignahead: Online Cross-Layer Knowledge Extraction on Graph Neural Networks.

Jiongyu Guo, Defang Chen, Can Wang

Proceedings of the International Joint Conference on Neural Networks, 2022

Confidence-Aware Multi-Teacher Knowledge Distillation.

Hailin Zhang, Defang Chen, Can Wang

Proceedings of the IEEE International Conference on Acoustics, 2022

Knowledge Distillation with the Reused Teacher Classifier.

Defang Chen, Jian-Ping Mei, Hailin Zhang, Can Wang, Yan Feng, Chun Chen

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Online Adversarial Distillation for Graph Neural Networks.

Can Wang, Zhe Wang, Defang Chen, Sheng Zhou, Yan Feng, Chun Chen

CoRR, 2021

Do We Need to Directly Access the Source Datasets for Domain Generalization?

Junkun Yuan, Xu Ma, Defang Chen, Kun Kuang, Fei Wu, Lanfen Lin

CoRR, 2021

Exploring the Connection between Knowledge Distillation and Logits Matching.

Defang Chen, Can Wang, Yan Feng, Chun Chen

CoRR, 2021

Distilling Holistic Knowledge with Graph Neural Networks.

Sheng Zhou, Yucheng Wang, Defang Chen, Jiawei Chen, Xin Wang, Can Wang, Jiajun Bu

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Cross-Layer Distillation with Semantic Calibration.

Defang Chen, Jian-Ping Mei, Yuan Zhang, Can Wang, Zhe Wang, Yan Feng, Chun Chen

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Online Knowledge Distillation via Multi-branch Diversity Enhancement.

Zheng Li, Ying Huang, Defang Chen, Tianren Luo, Ning Cai, Zhigeng Pan

Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

Online Knowledge Distillation with Diverse Peers.

Defang Chen, Jian-Ping Mei, Can Wang, Yan Feng, Chun Chen

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

HAHE: Hierarchical Attentive Heterogeneous Information Network Embedding.

Sheng Zhou, Jiajun Bu, Xin Wang, Jiawei Chen, Bingbing Hu, Defang Chen, Can Wang

CoRR, 2019