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2020 – today
- 2024
[j4]Lan Li, De-Chuan Zhan
, Xin-Chun Li:
Aligning model outputs for class imbalanced non-IID federated learning. Mach. Learn. 113(4): 1861-1884 (2024)- [j3]Xin-Chun Li, Shaoming Song, Yinchuan Li, Bingshuai Li, Yunfeng Shao, Yang Yang, De-Chuan Zhan:
MAP: Model Aggregation and Personalization in Federated Learning With Incomplete Classes. IEEE Trans. Knowl. Data Eng. 36(11): 6560-6573 (2024) - [c15]Yichu Xu, Xin-Chun Li, Le Gan, De-Chuan Zhan:
Weight Scope Alignment: A Frustratingly Easy Method for Model Merging. ECAI 2024: 1720-1727 - [c14]Bowen Tao, Lan Li, Xin-Chun Li, De-Chuan Zhan:
CLAF: Contrastive Learning with Augmented Features for Imbalanced Semi-Supervised Learning. ICASSP 2024: 7185-7189 - [c13]Wen-Shu Fan, Su Lu, Xin-Chun Li, De-Chuan Zhan, Le Gan:
Revisit the Essence of Distilling Knowledge through Calibration. ICML 2024 - [c12]Lan Li, Xin-Chun Li, Han-Jia Ye, De-Chuan Zhan:
Enhancing Class-Imbalanced Learning with Pre-Trained Guidance through Class-Conditional Knowledge Distillation. ICML 2024 - [c11]Bowen Tao, Xin-Chun Li, De-Chuan Zhan:
MLI Formula: A Nearly Scale-Invariant Solution with Noise Perturbation. ICML 2024 - [i12]Xin-Chun Li, Shaoming Song, Yinchuan Li, Bingshuai Li, Yunfeng Shao, Yang Yang, De-Chuan Zhan:
MAP: Model Aggregation and Personalization in Federated Learning with Incomplete Classes. CoRR abs/2404.09232 (2024) - [i11]Xin-Chun Li, Jin-Lin Tang, Bo Zhang, Lan Li, De-Chuan Zhan:
Exploring and Exploiting the Asymmetric Valley of Deep Neural Networks. CoRR abs/2405.12489 (2024) - [i10]Xin-Chun Li, Lan Li, De-Chuan Zhan:
Visualizing, Rethinking, and Mining the Loss Landscape of Deep Neural Networks. CoRR abs/2405.12493 (2024) - [i9]Xin-Chun Li, Wen-Shu Fan, Bowen Tao, Le Gan, De-Chuan Zhan:
Exploring Dark Knowledge under Various Teacher Capacities and Addressing Capacity Mismatch. CoRR abs/2405.13078 (2024) - [i8]Yichu Xu, Xin-Chun Li, Le Gan, De-Chuan Zhan:
Weight Scope Alignment: A Frustratingly Easy Method for Model Merging. CoRR abs/2408.12237 (2024) - 2023
- [j2]Xin-Chun Li, Yang Yang, De-Chuan Zhan:
MrTF: model refinery for transductive federated learning. Data Min. Knowl. Discov. 37(5): 2046-2069 (2023) - [i7]Xin-Chun Li, Yang Yang, De-Chuan Zhan:
MrTF: Model Refinery for Transductive Federated Learning. CoRR abs/2305.04201 (2023) - [i6]Bowen Tao, Lan Li, Xin-Chun Li, De-Chuan Zhan:
CLAF: Contrastive Learning with Augmented Features for Imbalanced Semi-Supervised Learning. CoRR abs/2312.09598 (2023) - 2022
- [c10]Xin-Chun Li, Yichu Xu, Shaoming Song, Bingshuai Li, Yinchuan Li, Yunfeng Shao, De-Chuan Zhan:
Federated Learning with Position-Aware Neurons. CVPR 2022: 10072-10081 - [c9]Xin-Chun Li, Yan-Jia Wang, Le Gan, De-Chuan Zhan:
Exploring Transferability Measures and Domain Selection in Cross-Domain Slot Filling. ICASSP 2022: 3758-3762 - [c8]Xin-Chun Li, Jin-Lin Tang, Shaoming Song, Bingshuai Li, Yinchuan Li, Yunfeng Shao, Le Gan, De-Chuan Zhan:
Avoid Overfitting User Specific Information in Federated Keyword Spotting. INTERSPEECH 2022: 3869-3873 - [c7]Xin-Chun Li, Wen-Shu Fan, Shaoming Song, Yinchuan Li, Bingshuai Li, Yunfeng Shao, De-Chuan Zhan:
Asymmetric Temperature Scaling Makes Larger Networks Teach Well Again. NeurIPS 2022 - [i5]Xin-Chun Li, Yi-Chu Xu, Shaoming Song, Bingshuai Li, Yinchuan Li, Yunfeng Shao, De-Chuan Zhan:
Federated Learning with Position-Aware Neurons. CoRR abs/2203.14666 (2022) - [i4]Xin-Chun Li, Jin-Lin Tang, Shaoming Song, Bingshuai Li, Yinchuan Li, Yunfeng Shao, Le Gan, De-Chuan Zhan:
Avoid Overfitting User Specific Information in Federated Keyword Spotting. CoRR abs/2206.08864 (2022) - [i3]Xin-Chun Li, Wen-Shu Fan, Shaoming Song, Yinchuan Li, Bingshuai Li, Yunfeng Shao, De-Chuan Zhan:
Asymmetric Temperature Scaling Makes Larger Networks Teach Well Again. CoRR abs/2210.04427 (2022) - 2021
- [j1]Xin-Chun Li, De-Chuan Zhan, Jia-Qi Yang, Yi Shi:
Deep multiple instance selection. Sci. China Inf. Sci. 64(3) (2021) - [c6]Han-Jia Ye, Xin-Chun Li, De-Chuan Zhan:
Task Cooperation for Semi-Supervised Few-Shot Learning. AAAI 2021: 10682-10690 - [c5]Xin-Chun Li, De-Chuan Zhan:
FedRS: Federated Learning with Restricted Softmax for Label Distribution Non-IID Data. KDD 2021: 995-1005 - [c4]Xin-Chun Li, De-Chuan Zhan, Yunfeng Shao, Bingshuai Li, Shaoming Song:
FedPHP: Federated Personalization with Inherited Private Models. ECML/PKDD (1) 2021: 587-602 - [i2]Xin-Chun Li, Le Gan, De-Chuan Zhan, Yunfeng Shao, Bingshuai Li, Shaoming Song:
Aggregate or Not? Exploring Where to Privatize in DNN Based Federated Learning Under Different Non-IID Scenes. CoRR abs/2107.11954 (2021) - [i1]Xin-Chun Li, De-Chuan Zhan, Yunfeng Shao, Bingshuai Li, Shaoming Song:
Preliminary Steps Towards Federated Sentiment Classification. CoRR abs/2107.11956 (2021) - 2020
- [c3]Jia-Qi Yang, De-Chuan Zhan, Xin-Chun Li:
Bottom-Up and Top-Down Graph Pooling. PAKDD (2) 2020: 568-579 - [c2]Xin-Chun Li, De-Chuan Zhan, Jia-Qi Yang, Yi Shi, Cheng Hang, Yi Lu:
Towards Understanding Transfer Learning Algorithms Using Meta Transfer Features. PAKDD (2) 2020: 855-866
2010 – 2019
- 2019
- [c1]Zhao-Yang Fu, De-Chuan Zhan, Xin-Chun Li, Yi-Xing Lu:
Automatic Successive Reinforcement Learning with Multiple Auxiliary Rewards. IJCAI 2019: 2336-2342
Coauthor Index
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