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2020 – today
- 2023
[j9]Han-Jia Ye
, Su Lu, De-Chuan Zhan:
Generalized Knowledge Distillation via Relationship Matching. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 1817-1834 (2023)- [j8]Han-Jia Ye, Lu Han, De-Chuan Zhan:
Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot Tasks. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 3721-3737 (2023) - [i27]Lu Han, Han-Jia Ye, De-Chuan Zhan:
On Pseudo-Labeling for Class-Mismatch Semi-Supervised Learning. CoRR abs/2301.06010 (2023) - [i26]Da-Wei Zhou, Qi-Wei Wang, Zhi-Hong Qi, Han-Jia Ye, De-Chuan Zhan, Ziwei Liu:
Deep Class-Incremental Learning: A Survey. CoRR abs/2302.03648 (2023) - [i25]Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan, Ziwei Liu:
Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need. CoRR abs/2303.07338 (2023) - 2022
- [c25]Da-Wei Zhou, Fu-Yun Wang, Han-Jia Ye, Liang Ma, Shiliang Pu, De-Chuan Zhan:
Forward Compatible Few-Shot Class-Incremental Learning. CVPR 2022: 9036-9046 - [c24]Han-Jia Ye, Yi Shi, De-Chuan Zhan:
Identifying Ambiguous Similarity Conditions via Semantic Matching. CVPR 2022: 16589-16598 - [c23]Fu-Yun Wang, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan:
FOSTER: Feature Boosting and Compression for Class-Incremental Learning. ECCV (25) 2022: 398-414 - [c22]Han-Jia Ye, Wei-Lun Chao:
How to Train Your MAML to Excel in Few-Shot Classification. ICLR 2022 - [c21]Yi-Kai Zhang, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan:
Audio-Visual Generalized Few-Shot Learning with Prototype-Based Co-Adaptation. INTERSPEECH 2022: 531-535 - [i24]Da-Wei Zhou, Fu-Yun Wang, Han-Jia Ye, Liang Ma, Shiliang Pu, De-Chuan Zhan:
Forward Compatible Few-Shot Class-Incremental Learning. CoRR abs/2203.06953 (2022) - [i23]Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan:
Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks. CoRR abs/2203.17030 (2022) - [i22]Han-Jia Ye, Yi Shi, De-Chuan Zhan:
Identifying Ambiguous Similarity Conditions via Semantic Matching. CoRR abs/2204.04053 (2022) - [i21]Fu-Yun Wang, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan:
FOSTER: Feature Boosting and Compression for Class-Incremental Learning. CoRR abs/2204.04662 (2022) - [i20]Su Lu, Han-Jia Ye, De-Chuan Zhan:
Faculty Distillation with Optimal Transport. CoRR abs/2204.11526 (2022) - [i19]Han-Jia Ye, Su Lu, De-Chuan Zhan:
Generalized Knowledge Distillation via Relationship Matching. CoRR abs/2205.01915 (2022) - [i18]Da-Wei Zhou, Qi-Wei Wang, Han-Jia Ye, De-Chuan Zhan:
A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning. CoRR abs/2205.13218 (2022) - [i17]Lu Han, Han-Jia Ye, De-Chuan Zhan:
Contrastive Principal Component Learning: Modeling Similarity by Augmentation Overlap. CoRR abs/2206.00471 (2022) - 2021
- [j7]Han-Jia Ye, Hexiang Hu, De-Chuan Zhan:
Learning Adaptive Classifiers Synthesis for Generalized Few-Shot Learning. Int. J. Comput. Vis. 129(6): 1930-1953 (2021) - [j6]Han-Jia Ye, De-Chuan Zhan, Yuan Jiang, Zhi-Hua Zhou:
Heterogeneous Few-Shot Model Rectification With Semantic Mapping. IEEE Trans. Pattern Anal. Mach. Intell. 43(11): 3878-3891 (2021) - [j5]Xiu-Shen Wei, Han-Jia Ye, Xin Mu, Jianxin Wu, Chunhua Shen, Zhi-Hua Zhou:
Multi-Instance Learning With Emerging Novel Class. IEEE Trans. Knowl. Data Eng. 33(5): 2109-2120 (2021) - [c20]Haoyue Bai, Rui Sun, Lanqing Hong, Fengwei Zhou, Nanyang Ye, Han-Jia Ye, S.-H. Gary Chan, Zhenguo Li:
DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic Augmentation. AAAI 2021: 6705-6713 - [c19]Su Lu, Han-Jia Ye, De-Chuan Zhan:
Tailoring Embedding Function to Heterogeneous Few-Shot Tasks by Global and Local Feature Adaptors. AAAI 2021: 8776-8783 - [c18]Han-Jia Ye, Xin-Chun Li, De-Chuan Zhan:
Task Cooperation for Semi-Supervised Few-Shot Learning. AAAI 2021: 10682-10690 - [c17]Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan:
Learning Placeholders for Open-Set Recognition. CVPR 2021: 4401-4410 - [c16]Han-Jia Ye, De-Chuan Zhan, Wei-Lun Chao:
Procrustean Training for Imbalanced Deep Learning. ICCV 2021: 92-102 - [c15]Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan:
Co-Transport for Class-Incremental Learning. ACM Multimedia 2021: 1645-1654 - [c14]Xiu-Shen Wei, Jufeng Yang, Han-Jia Ye, Jian Yang:
MULL'21: First International Workshop on Multimedia Understanding with Less Labeling. ACM Multimedia 2021: 5704-5705 - [c13]Xiu-Shen Wei, Yang Shen, Xuhao Sun, Han-Jia Ye, Jian Yang:
A$^2$-Net: Learning Attribute-Aware Hash Codes for Large-Scale Fine-Grained Image Retrieval. NeurIPS 2021: 5720-5730 - [c12]Su Lu, Han-Jia Ye, Le Gan, De-Chuan Zhan:
Towards Enabling Meta-Learning from Target Models. NeurIPS 2021: 8060-8071 - [e1]Xiu-Shen Wei, Han-Jia Ye, Jufeng Yang, Jian Yang:
MULL'21: Multimedia Understanding with Less Labeling on Multimedia Understanding with Less Labeling, Virtual Event, China, 24 October 2021. ACM 2021, ISBN 978-1-4503-8681-4 [contents] - [i16]Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan:
Learning Placeholders for Open-Set Recognition. CoRR abs/2103.15086 (2021) - [i15]Han-Jia Ye, De-Chuan Zhan, Wei-Lun Chao:
Procrustean Training for Imbalanced Deep Learning. CoRR abs/2104.01769 (2021) - [i14]Su Lu, Han-Jia Ye, De-Chuan Zhan:
Support-Target Protocol for Meta-Learning. CoRR abs/2104.03736 (2021) - [i13]Su Lu, Han-Jia Ye, De-Chuan Zhan:
Few-Shot Action Recognition with Compromised Metric via Optimal Transport. CoRR abs/2104.03737 (2021) - [i12]Han-Jia Ye, Da-Wei Zhou, Lanqing Hong, Zhenguo Li, Xiu-Shen Wei, De-Chuan Zhan:
Contextualizing Multiple Tasks via Learning to Decompose. CoRR abs/2106.08112 (2021) - [i11]Han-Jia Ye, Wei-Lun Chao:
How to Train Your MAML to Excel in Few-Shot Classification. CoRR abs/2106.16245 (2021) - [i10]Han-Jia Ye, Lu Ming, De-Chuan Zhan, Wei-Lun Chao:
Few-Shot Learning with a Strong Teacher. CoRR abs/2107.00197 (2021) - [i9]Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan:
Co-Transport for Class-Incremental Learning. CoRR abs/2107.12654 (2021) - [i8]Da-Wei Zhou, Fu-Yun Wang, Han-Jia Ye, De-Chuan Zhan:
PyCIL: A Python Toolbox for Class-Incremental Learning. CoRR abs/2112.12533 (2021) - 2020
- [j4]Han-Jia Ye, Xiang-Rong Sheng, De-Chuan Zhan:
Few-shot learning with adaptively initialized task optimizer: a practical meta-learning approach. Mach. Learn. 109(3): 643-664 (2020) - [j3]Han-Jia Ye, De-Chuan Zhan, Nan Li, Yuan Jiang:
Learning Multiple Local Metrics: Global Consideration Helps. IEEE Trans. Pattern Anal. Mach. Intell. 42(7): 1698-1712 (2020) - [c11]Han-Jia Ye, Hexiang Hu, De-Chuan Zhan, Fei Sha:
Few-Shot Learning via Embedding Adaptation With Set-to-Set Functions. CVPR 2020: 8805-8814 - [c10]Han-Jia Ye, Su Lu, De-Chuan Zhan:
Distilling Cross-Task Knowledge via Relationship Matching. CVPR 2020: 12393-12402 - [i7]Han-Jia Ye, Hong-You Chen, De-Chuan Zhan, Wei-Lun Chao:
Identifying and Compensating for Feature Deviation in Imbalanced Deep Learning. CoRR abs/2001.01385 (2020) - [i6]Wei-Lun Chao, Han-Jia Ye, De-Chuan Zhan, Mark E. Campbell, Kilian Q. Weinberger:
Revisiting Meta-Learning as Supervised Learning. CoRR abs/2002.00573 (2020) - [i5]Chao Wang, Ruo-Ze Liu, Han-Jia Ye, Yang Yu:
Novelty-Prepared Few-Shot Classification. CoRR abs/2003.00497 (2020) - [i4]Han-Jia Ye, Lu Han, De-Chuan Zhan:
Revisiting Unsupervised Meta-Learning: Amplifying or Compensating for the Characteristics of Few-Shot Tasks. CoRR abs/2011.14663 (2020) - [i3]Haoyue Bai, Rui Sun, Lanqing Hong, Fengwei Zhou, Nanyang Ye, Han-Jia Ye, S.-H. Gary Chan, Zhenguo Li:
DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic Augmentation. CoRR abs/2012.09382 (2020)
2010 – 2019
- 2019
- [j2]Han-Jia Ye, De-Chuan Zhan, Yuan Jiang:
Fast generalization rates for distance metric learning. Mach. Learn. 108(2): 267-295 (2019) - [j1]Han-Jia Ye, De-Chuan Zhan, Yuan Jiang, Zhi-Hua Zhou:
What Makes Objects Similar: A Unified Multi-Metric Learning Approach. IEEE Trans. Pattern Anal. Mach. Intell. 41(5): 1257-1270 (2019) - [i2]Han-Jia Ye, Hexiang Hu, De-Chuan Zhan, Fei Sha:
Learning Classifier Synthesis for Generalized Few-Shot Learning. CoRR abs/1906.02944 (2019) - 2018
- [c9]Han-Jia Ye, De-Chuan Zhan, Yuan Jiang, Zhi-Hua Zhou:
Rectify Heterogeneous Models with Semantic Mapping. ICML 2018: 1904-1913 - [c8]Han-Jia Ye, Xiang-Rong Sheng, De-Chuan Zhan, Peng He:
Distance Metric Facilitated Transportation between Heterogeneous Domains. IJCAI 2018: 3012-3018 - [i1]Han-Jia Ye, Hexiang Hu, De-Chuan Zhan, Fei Sha:
Learning Embedding Adaptation for Few-Shot Learning. CoRR abs/1812.03664 (2018) - 2017
- [c7]Han-Jia Ye, De-Chuan Zhan, Xue-Min Si, Yuan Jiang:
Learning Mahalanobis Distance Metric: Considering Instance Disturbance Helps. IJCAI 2017: 3315-3321 - 2016
- [c6]Han-Jia Ye, De-Chuan Zhan, Yuan Jiang:
Instance Specific Metric Subspace Learning: A Bayesian Approach. AAAI 2016: 2272-2278 - [c5]Han-Jia Ye, De-Chuan Zhan, Xue-Min Si, Yuan Jiang:
Learning Feature Aware Metric. ACML 2016: 286-301 - [c4]Han-Jia Ye, De-Chuan Zhan, Xiaolin Li, Zhen-Chuan Huang, Yuan Jiang:
College Student Scholarships and Subsidies Granting: A Multi-modal Multi-label Approach. ICDM 2016: 559-568 - [c3]Han-Jia Ye, De-Chuan Zhan, Xue-Min Si, Yuan Jiang, Zhi-Hua Zhou:
What Makes Objects Similar: A Unified Multi-Metric Learning Approach. NIPS 2016: 1235-1243 - 2015
- [c2]Han-Jia Ye, De-Chuan Zhan, Yuan Miao, Yuan Jiang, Zhi-Hua Zhou:
Rank Consistency based Multi-View Learning: A Privacy-Preserving Approach. CIKM 2015: 991-1000 - [c1]Yang Yang, Han-Jia Ye, De-Chuan Zhan, Yuan Jiang:
Auxiliary Information Regularized Machine for Multiple Modality Feature Learning. IJCAI 2015: 1033-1039
Coauthor Index
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last updated on 2023-03-17 20:42 CET by the dblp team
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