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ORCIDJialiang Tang
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- affiliation: Southwest University, Chongqing, China
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2020 – today
- 2024
[j3]Jialiang Tang
, Ning Jiang, Hongyuan Zhu, Joey Tianyi Zhou, Chen Gong:
Learning Student Network Under Universal Label Noise. IEEE Trans. Image Process. 33: 4363-4376 (2024)- [c33]Jialiang Tang, Shuo Chen, Gang Niu, Hongyuan Zhu, Joey Tianyi Zhou, Chen Gong, Masashi Sugiyama:
Direct Distillation Between Different Domains. ECCV (80) 2024: 154-172 - [c32]Xinlei Huang, Ning Jiang, Jialiang Tang:
ClearKD: Clear Knowledge Distillation for Medical Image Classification. IJCNN 2024: 1-8 - [c31]Xin Cheng, Jialiang Tang, Zhiqiang Zhang, Wenxin Yu, Ning Jiang, Jinjia Zhou:
Decoupled Multi-teacher Knowledge Distillation based on Entropy. ISCAS 2024: 1-5 - [c30]Lebin Li, Ning Jiang, Jialiang Tang, Xinlei Huang:
Amalgamating Knowledge for Comprehensive Classification with Uncertainty Suppression. ISCAS 2024: 1-5 - [c29]Ruijian Xu, Ning Jiang, Jialiang Tang, Xinlei Huang:
Adaptive Informative Semantic Knowledge Transfer for Knowledge Distillation. ISCAS 2024: 1-5 - [i3]Jialiang Tang, Shuo Chen, Gang Niu, Hongyuan Zhu, Joey Tianyi Zhou, Chen Gong, Masashi Sugiyama:
Direct Distillation between Different Domains. CoRR abs/2401.06826 (2024) - [i2]Xinlei Huang, Jialiang Tang, Xubin Zheng, Jinjia Zhou, Wenxin Yu, Ning Jiang:
Learn from Balance: Rectifying Knowledge Transfer for Long-Tailed Scenarios. CoRR abs/2409.07694 (2024) - 2023
- [j2]Ning Jiang, Jialiang Tang, Wenxin Yu:
Positive-Unlabeled Learning for Knowledge Distillation. Neural Process. Lett. 55(3): 2613-2631 (2023) - [c28]Jialiang Tang, Shuo Chen, Gang Niu, Masashi Sugiyama, Chen Gong:
Distribution Shift Matters for Knowledge Distillation with Webly Collected Images. ICCV 2023: 17424-17434 - [c27]Haifeng Qing, Ning Jiang, Jialiang Tang, Xinlei Huang, Wengqing Wu:
Joint Regularization Knowledge Distillation. ICONIP (12) 2023: 173-184 - [c26]Cheng Lin, Ning Jiang, Jialiang Tang, Xinlei Huang, Wenqing Wu:
Dy-KD: Dynamic Knowledge Distillation for Reduced Easy Examples. ICONIP (12) 2023: 223-234 - [c25]Cheng Lin, Ning Jiang, Jialiang Tang, Xinlei Huang:
Feature Reconstruction Distillation with Self-attention. ICONIP (12) 2023: 246-257 - [c24]Xinlei Huang, Ning Jiang, Jialiang Tang, Wenqing Wu:
Dynamic Feature Distillation. ICONIP (13) 2023: 402-413 - [c23]Honglin Zhu, Ning Jiang, Jialiang Tang, Xinlei Huang:
Knowledge Distillation via Information Matching. ICONIP (4) 2023: 405-417 - [c22]Luyao Shi, Ning Jiang, Jialiang Tang, Xinlei Huang:
Correlation Guided Multi-teacher Knowledge Distillation. ICONIP (4) 2023: 562-574 - [i1]Jialiang Tang, Shuo Chen, Gang Niu, Masashi Sugiyama, Chen Gong:
Distribution Shift Matters for Knowledge Distillation with Webly Collected Images. CoRR abs/2307.11469 (2023) - 2022
- [c21]Haifeng Qing, Jialiang Tang, Xiaoyan Yang, Xinlei Huang, Honglin Zhu, Ning Jiang:
Stimulates Potential for Knowledge Distillation. ICANN (4) 2022: 187-198 - [c20]Jiawei Sun, Ning Jiang, Jialiang Tang:
Cut-controller: An Effective Framework for Chinese Text Classification. ICMSSP 2022: 74-79 - [c19]Honglin Zhu, Ning Jiang, Jialiang Tang, Xinlei Huang, Haifeng Qing, Wenqing Wu, Peng Zhang:
Cross-Layer Fusion for Feature Distillation. ICONIP (4) 2022: 433-445 - [c18]Xinlei Huang, Jialiang Tang, Haifeng Qing, Honglin Zhu, Ning Jiang, Wenqing Wu, Peng Zhang:
Optimizing Knowledge Distillation via Shallow Texture Knowledge Transfer. ICONIP (4) 2022: 647-658 - [c17]Mingjin Liu, Wenxin Yu, Jialiang Tang, Ning Jiang, Kang Xu, Chang Liu:
Improve 3D Feature Extraction and Fusion for Stage Diagnosis of Alzheimer's Disease. ISCAS 2022: 2358-2362 - 2021
- [c16]Jialiang Tang, Ning Jiang, Wenxin Yu:
Gradient Local Binary Pattern For Convolutional Neural Networks. ICIP 2021: 744-748 - [c15]Jiarui Cheng, Ning Jiang, Jialiang Tang, Xin Deng, Wenxin Yu, Peng Zhang:
Using a Two-Stage GAN to Learn Image Degradation for Image Super-Resolution. ICONIP (5) 2021: 222-230 - [c14]Jialiang Tang, Xiaoyan Yang, Xin Cheng, Ning Jiang, Wenxin Yu, Peng Zhang:
Data-Free Knowledge Distillation with Positive-Unlabeled Learning. ICONIP (2) 2021: 309-320 - [c13]Jialiang Tang, Xiaoyan Yang, Xin Cheng, Ning Jiang, Wenxin Yu, Peng Zhang:
Consistent Knowledge Distillation Based on Siamese Networks. ICONIP (5) 2021: 326-333 - [c12]Mingjin Liu, Jialiang Tang, Wenxin Yu, Ning Jiang:
Attention-Based 3D ResNet for Detection of Alzheimer's Disease Process. ICONIP (1) 2021: 342-353 - [c11]Ning Jiang, Jialiang Tang, Xiaoyan Yang, Wenxin Yu, Peng Zhang:
Improving Shallow Neural Networks via Local and Global Normalization. ICONIP (1) 2021: 596-608 - [c10]Xiaoyan Yang, Jialiang Tang, Ning Jiang, Wenxin Yu, Peng Zhang:
Triplet Mapping for Continuously Knowledge Distillation. ICONIP (1) 2021: 669-680 - [c9]Jialiang Tang, Ning Jiang, Wenxin Yu, Wenqin Wu:
Triplet Knowledge Distillation Networks for Model Compression. IJCNN 2021: 1-8 - [c8]Huan Cai, Jialiang Tang, Yihan Wu, Min Xia, Gang He, Yangsong Zhang:
The Detection of Attentive Mental State Using a Mixed Neural Network Model. ISCAS 2021: 1-5 - [c7]Ning Jiang, Jialiang Tang, Wenxin Yu, Jinjia Zhou, Liuwei Mai:
Gradient Local Binary Pattern Layer to Initialize the Convolutional Neural Networks. ISCAS 2021: 1-5 - [c6]Jialiang Tang, Mingjin Liu, Ning Jiang, Huan Cai, Wenxin Yu, Jinjia Zhou:
Data-Free Network Pruning for Model Compression. ISCAS 2021: 1-5 - [c5]Jialiang Tang, Mingjin Liu, Ning Jiang, Wenxin Yu, Changzheng Yang:
Spatial and Channel Dimensions Attention Feature Transfer for Better Convolutional Neural Networks. ISCAS 2021: 1-5 - [c4]Jialiang Tang, Mingjin Liu, Ning Jiang, Wenxin Yu, Changzheng Yang, Jinjia Zhou:
Knowledge Distillation Based on Positive-Unlabeled Classification and Attention Mechanism. ISCAS 2021: 1-5 - [c3]Ning Jiang, Jialiang Tang, Wenxin Yu, Jinjia Zhou:
Local Feature Normalization. KSEM 2021: 228-239 - 2020
- [j1]Jialiang Tang, Ning Jiang, Wenxin Yu, Jinjia Zhou, Liuwei Mai:
Two-Stage Model Compression and Acceleration: Optimal Student Network for Better Performance. IEEE Access 8: 217816-217829 (2020) - [c2]Zhiqiang Zhang, Wenxin Yu, Jinjia Zhou, Xuewen Zhang, Jialiang Tang, Siyuan Li, Ning Jiang, Gang He, Gang He, Zhuo Yang:
Customizable GAN: Customizable Image Synthesis Based on Adversarial Learning. ICONIP (4) 2020: 336-344 - [c1]Ning Jiang, Jialiang Tang, Zhiqiang Zhang, Wenxin Yu, Xin Deng, Jinjia Zhou:
Search-and-Train: Two-Stage Model Compression and Acceleration. ICONIP (5) 2020: 642-649
Coauthor Index
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