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Defang Chen 0001
Person information
- affiliation: Zhejiang University, Hangzhou, Zhejiang, CN
Other persons with the same name
- Defang Chen — disambiguation page
- Defang Chen 0002 — East China University of Science and Technology, Shanghai, China
- Defang Chen 0003 — Shandong University, Jinan, China
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2020 – today
- 2024
- [j9]Can Wang, Zhe Wang, Defang Chen
, Sheng Zhou
Online adversarial knowledge distillation for graph neural networks. Expert Syst. Appl. 237(Part C): 121671 (2024) - [j8]Wujie Sun
Multi-exit self-distillation with appropriate teachers. Frontiers Inf. Technol. Electron. Eng. 25(4): 585-599 (2024) - [j7]Jian-Ping Mei
Output Regularization With Cluster-Based Soft Targets. IEEE Trans. Neural Networks Learn. Syst. 35(8): 11463-11474 (2024) - [c17]Yichen Liu
Confidence-aware Self-Semantic Distillation on Knowledge Graph Embedding. CIKM 2024: 1493-1502 - [c16]Zhenyu Zhou, Defang Chen, Can Wang, Chun Chen:
Fast ODE-based Sampling for Diffusion Models in Around 5 Steps. CVPR 2024: 7777-7786 - [c15]Defang Chen, Zhenyu Zhou, Can Wang, Chunhua Shen, Siwei Lyu:
On the Trajectory Regularity of ODE-based Diffusion Sampling. ICML 2024 - [i26]Wujie Sun, Defang Chen, Jiawei Chen, Yan Feng, Chun Chen, Can Wang:
Knowledge Translation: A New Pathway for Model Compression. CoRR abs/2401.05772 (2024) - [i25]Defang Chen, Zhenyu Zhou, Can Wang, Chunhua Shen, Siwei Lyu:
On the Trajectory Regularity of ODE-based Diffusion Sampling. CoRR abs/2405.11326 (2024) - [i24]Wujie Sun, Defang Chen, Siwei Lyu, Genlang Chen, Chun Chen, Can Wang:
Knowledge Distillation with Refined Logits. CoRR abs/2408.07703 (2024) - [i23]Zheyuan Zhan, Defang Chen, Jian-Ping Mei, Zhenghe Zhao, Jiawei Chen, Chun Chen, Siwei Lyu, Can Wang:
Conditional Image Synthesis with Diffusion Models: A Survey. CoRR abs/2409.19365 (2024) - [i22]Zhenyu Zhou, Defang Chen, Can Wang, Chun Chen, Siwei Lyu:
Simple and Fast Distillation of Diffusion Models. CoRR abs/2409.19681 (2024) - 2023
- [j6]Junkun Yuan
Domain-Specific Bias Filtering for Single Labeled Domain Generalization. Int. J. Comput. Vis. 131(2): 552-571 (2023) - [j5]Jian-Ping Mei
Finalizing your reference list with machine learning. J. Ambient Intell. Humaniz. Comput. 14(11): 14883-14892 (2023) - [j4]Jiongyu Guo, Defang Chen, Can Wang:
Online cross-layer knowledge distillation on graph neural networks with deep supervision. Neural Comput. Appl. 35(30): 22359-22374 (2023) - [j3]Can Wang
SemCKD: Semantic Calibration for Cross-Layer Knowledge Distillation. IEEE Trans. Knowl. Data Eng. 35(6): 6305-6319 (2023) - [j2]Junkun Yuan
Collaborative Semantic Aggregation and Calibration for Federated Domain Generalization. IEEE Trans. Knowl. Data Eng. 35(12): 12528-12541 (2023) - [c14]Wujie Sun, Defang Chen, Can Wang, Deshi Ye, Yan Feng, Chun Chen:
Holistic Weighted Distillation for Semantic Segmentation. ICME 2023: 396-401 - [c13]Wujie Sun, Defang Chen, Can Wang, Deshi Ye, Yan Feng, Chun Chen:
Accelerating Diffusion Sampling with Classifier-based Feature Distillation. ICME 2023: 810-815 - [c12]Shiya Luo, Defang Chen, Can Wang:
Customizing Synthetic Data for Data-Free Student Learning. ICME 2023: 1817-1822 - [c11]Hailin Zhang, Defang Chen, Can Wang:
Adaptive Multi-Teacher Knowledge Distillation with Meta-Learning. ICME 2023: 1943-1948 - [c10]Shiya Luo, Defang Chen, Can Wang:
Knowledge Distillation with Deep Supervision. IJCNN 2023: 1-8 - [i21]Defang Chen, Zhenyu Zhou, Jian-Ping Mei, Chunhua Shen, Chun Chen, Can Wang:
A Geometric Perspective on Diffusion Models. CoRR abs/2305.19947 (2023) - [i20]Hailin Zhang, Defang Chen, Can Wang:
Adaptive Multi-Teacher Knowledge Distillation with Meta-Learning. CoRR abs/2306.06634 (2023) - [i19]Shiya Luo, Defang Chen, Can Wang:
Customizing Synthetic Data for Data-Free Student Learning. CoRR abs/2307.04542 (2023) - [i18]Zhenyu Zhou, Defang Chen, Can Wang, Chun Chen:
Fast ODE-based Sampling for Diffusion Models in Around 5 Steps. CoRR abs/2312.00094 (2023) - 2022
- [j1]Zhehui Zhou, Can Wang, Yan Feng, Defang Chen
JointE: Jointly utilizing 1D and 2D convolution for knowledge graph embedding. Knowl. Based Syst. 240: 108100 (2022) - [c9]Defang Chen, Jian-Ping Mei, Hailin Zhang, Can Wang, Yan Feng, Chun Chen:
Knowledge Distillation with the Reused Teacher Classifier. CVPR 2022: 11923-11932 - [c8]Hailin Zhang, Defang Chen, Can Wang:
Confidence-Aware Multi-Teacher Knowledge Distillation. ICASSP 2022: 4498-4502 - [c7]Jiongyu Guo, Defang Chen, Can Wang:
Alignahead: Online Cross-Layer Knowledge Extraction on Graph Neural Networks. IJCNN 2022: 1-8 - [c6]Junkun Yuan, Xu Ma, Defang Chen, Kun Kuang, Fei Wu, Lanfen Lin:
Label-Efficient Domain Generalization via Collaborative Exploration and Generalization. ACM Multimedia 2022: 2361-2370 - [c5]Can Wang, Sheng Zhou, Kang Yu, Defang Chen, Bolang Li, Yan Feng, Chun Chen:
Collaborative Knowledge Distillation for Heterogeneous Information Network Embedding. WWW 2022: 1631-1639 - [i17]Hailin Zhang, Defang Chen
Confidence-Aware Multi-Teacher Knowledge Distillation. CoRR abs/2201.00007 (2022) - [i16]Shiya Luo, Defang Chen, Can Wang:
Deeply-Supervised Knowledge Distillation. CoRR abs/2202.07846 (2022) - [i15]Defang Chen, Jian-Ping Mei, Hailin Zhang, Can Wang, Yan Feng, Chun Chen:
Knowledge Distillation with the Reused Teacher Classifier. CoRR abs/2203.14001 (2022) - [i14]Jiongyu Guo, Defang Chen, Can Wang:
Alignahead: Online Cross-Layer Knowledge Extraction on Graph Neural Networks. CoRR abs/2205.02468 (2022) - [i13]Zhehui Zhou, Defang Chen, Can Wang, Yan Feng, Chun Chen:
Improving Knowledge Graph Embedding via Iterative Self-Semantic Knowledge Distillation. CoRR abs/2206.02963 (2022) - [i12]Junkun Yuan, Xu Ma, Defang Chen, Kun Kuang, Fei Wu, Lanfen Lin:
Label-Efficient Domain Generalization via Collaborative Exploration and Generalization. CoRR abs/2208.03644 (2022) - [i11]Jiongyu Guo, Defang Chen, Can Wang:
Online Cross-Layer Knowledge Distillation on Graph Neural Networks with Deep Supervision. CoRR abs/2210.13743 (2022) - [i10]Wujie Sun, Defang Chen, Can Wang, Deshi Ye, Yan Feng, Chun Chen:
Accelerating Diffusion Sampling with Classifier-based Feature Distillation. CoRR abs/2211.12039 (2022) - 2021
- [c4]Defang Chen, Jian-Ping Mei, Yuan Zhang, Can Wang, Zhe Wang, Yan Feng, Chun Chen:
Cross-Layer Distillation with Semantic Calibration. AAAI 2021: 7028-7036 - [c3]Sheng Zhou, Yucheng Wang, Defang Chen, Jiawei Chen, Xin Wang, Can Wang, Jiajun Bu:
Distilling Holistic Knowledge with Graph Neural Networks. ICCV 2021: 10367-10376 - [i9]Sheng Zhou, Yucheng Wang, Defang Chen, Jiawei Chen, Xin Wang, Can Wang, Jiajun Bu:
Distilling Holistic Knowledge with Graph Neural Networks. CoRR abs/2108.05507 (2021) - [i8]Defang Chen
Exploring the Connection between Knowledge Distillation and Logits Matching. CoRR abs/2109.06458 (2021) - [i7]Junkun Yuan, Xu Ma, Defang Chen, Kun Kuang, Fei Wu, Lanfen Lin:
Domain-Specific Bias Filtering for Single Labeled Domain Generalization. CoRR abs/2110.00726 (2021) - [i6]Junkun Yuan, Xu Ma, Defang Chen, Kun Kuang, Fei Wu, Lanfen Lin:
Do We Need to Directly Access the Source Datasets for Domain Generalization? CoRR abs/2110.06736 (2021) - [i5]Can Wang, Zhe Wang, Defang Chen, Sheng Zhou, Yan Feng, Chun Chen:
Online Adversarial Distillation for Graph Neural Networks. CoRR abs/2112.13966 (2021) - 2020
- [c2]Defang Chen, Jian-Ping Mei, Can Wang, Yan Feng, Chun Chen:
Online Knowledge Distillation with Diverse Peers. AAAI 2020: 3430-3437 - [c1]Zheng Li
Online Knowledge Distillation via Multi-branch Diversity Enhancement. ACCV (4) 2020: 318-333 - [i4]Zheng Li, Ying Huang, Defang Chen, Tianren Luo, Ning Cai, Zhigeng Pan:
Online Knowledge Distillation via Multi-branch Diversity Enhancement. CoRR abs/2010.00795 (2020) - [i3]Defang Chen
Cross-Layer Distillation with Semantic Calibration. CoRR abs/2012.03236 (2020)
2010 – 2019
- 2019
- [i2]Sheng Zhou, Jiajun Bu, Xin Wang, Jiawei Chen, Bingbing Hu, Defang Chen, Can Wang:
HAHE: Hierarchical Attentive Heterogeneous Information Network Embedding. CoRR abs/1902.01475 (2019) - [i1]Defang Chen
Online Knowledge Distillation with Diverse Peers. CoRR abs/1912.00350 (2019)
Coauthor Index
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last updated on 2024-12-02 21:28 CET by the dblp team
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