De-Chuan Zhan

According to our database, De-Chuan Zhan authored at least 134 papers between 2005 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Aligning model outputs for class imbalanced non-IID federated learning.

Lan Li, De-Chuan Zhan, Xin-Chun Li

Mach. Learn., April, 2024

Few-Shot Learning With a Strong Teacher.

Han-Jia Ye, Lu Ming, De-Chuan Zhan, Wei-Lun Chao

IEEE Trans. Pattern Anal. Mach. Intell., March, 2024

Contextualizing Meta-Learning via Learning to Decompose.

Han-Jia Ye, Da-Wei Zhou, Lanqing Hong, Zhenguo Li, Xiu-Shen Wei, De-Chuan Zhan

IEEE Trans. Pattern Anal. Mach. Intell., January, 2024

Bridge the Modality and Capacity Gaps in Vision-Language Model Selection.

Chao Yi, De-Chuan Zhan, Han-Jia Ye

CoRR, 2024

Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning.

Da-Wei Zhou, Hai-Long Sun, Han-Jia Ye, De-Chuan Zhan

CoRR, 2024

AD3: Implicit Action is the Key for World Models to Distinguish the Diverse Visual Distractors.

Yucen Wang, Shenghua Wan, Le Gan, Shuai Feng, De-Chuan Zhan

CoRR, 2024

Continual Learning with Pre-Trained Models: A Survey.

Da-Wei Zhou, Hai-Long Sun, Jingyi Ning, Han-Jia Ye, De-Chuan Zhan

CoRR, 2024

Twice Class Bias Correction for Imbalanced Semi-supervised Learning.

Lan Li, Bowen Tao, Lu Han, De-Chuan Zhan, Han-Jia Ye

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Deep visual-linguistic fusion network considering cross-modal inconsistency for rumor detection.

Yang Yang, Ran Bao, Weili Guo, De-Chuan Zhan, Yilong Yin, Jian Yang

Sci. China Inf. Sci., December, 2023

Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks.

Da-Wei Zhou, Han-Jia Ye, Liang Ma, Di Xie, Shiliang Pu, De-Chuan Zhan

IEEE Trans. Pattern Anal. Mach. Intell., November, 2023

MrTF: model refinery for transductive federated learning.

Xin-Chun Li, Yang Yang, De-Chuan Zhan

Data Min. Knowl. Discov., September, 2023

PyCIL: a Python toolbox for class-incremental learning.

Da-Wei Zhou, Fu-Yun Wang, Han-Jia Ye, De-Chuan Zhan

Sci. China Inf. Sci., September, 2023

Cost-Effective Incremental Deep Model: Matching Model Capacity With the Least Sampling.

Yang Yang, Da-Wei Zhou, De-Chuan Zhan, Hui Xiong, Yuan Jiang, Jian Yang

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

Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot Tasks.

Han-Jia Ye, Lu Han, De-Chuan Zhan

IEEE Trans. Pattern Anal. Mach. Intell., March, 2023

Corporate Relative Valuation Using Heterogeneous Multi-Modal Graph Neural Network.

Yang Yang, Jia-Qi Yang, Ran Bao, De-Chuan Zhan, Hengshu Zhu, Xiaoru Gao, Hui Xiong, Jian Yang

IEEE Trans. Knowl. Data Eng., 2023

Generalized Knowledge Distillation via Relationship Matching.

Han-Jia Ye, Su Lu, De-Chuan Zhan

IEEE Trans. Pattern Anal. Mach. Intell., 2023

CLAF: Contrastive Learning with Augmented Features for Imbalanced Semi-Supervised Learning.

Bowen Tao, Lan Li, Xin-Chun Li, De-Chuan Zhan

CoRR, 2023

Learning Robust Precipitation Forecaster by Temporal Frame Interpolation.

Lu Han, Xu-Yang Chen, Han-Jia Ye, De-Chuan Zhan

CoRR, 2023

Training-Free Generalization on Heterogeneous Tabular Data via Meta-Representation.

Han-Jia Ye, Qi-Le Zhou, De-Chuan Zhan

CoRR, 2023

Unlocking the Transferability of Tokens in Deep Models for Tabular Data.

Qi-Le Zhou, Han-Jia Ye, Leye Wang, De-Chuan Zhan

CoRR, 2023

REFORM: Removing False Correlation in Multi-level Interaction for CTR Prediction.

Songli Wu, Liang Du, Jia-Qi Yang, Yuai Wang, De-Chuan Zhan, Shuang Zhao, Zixun Sun

CoRR, 2023

PILOT: A Pre-Trained Model-Based Continual Learning Toolbox.

Hai-Long Sun, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan

CoRR, 2023

ZhiJian: A Unifying and Rapidly Deployable Toolbox for Pre-trained Model Reuse.

Yi-Kai Zhang, Lu Ren, Chao Yi, Qi-Wei Wang, De-Chuan Zhan, Han-Jia Ye

CoRR, 2023

Streaming CTR Prediction: Rethinking Recommendation Task for Real-World Streaming Data.

Qi-Wei Wang, Hongyu Lu, Yu Chen, Da-Wei Zhou, De-Chuan Zhan, Ming Chen, Han-Jia Ye

CoRR, 2023

COURIER: Contrastive User Intention Reconstruction for Large-Scale Pre-Train of Image Features.

Jia-Qi Yang, Chenglei Dai, Dan Ou, Ju Huang, De-Chuan Zhan, Qingwen Liu, Xiaoyi Zeng, Yang Yang

CoRR, 2023

Beyond Probability Partitions: Calibrating Neural Networks with Semantic Aware Grouping.

Jia-Qi Yang, De-Chuan Zhan, Le Gan

CoRR, 2023

Learning without Forgetting for Vision-Language Models.

Da-Wei Zhou, Yuanhan Zhang, Jingyi Ning, Han-Jia Ye, De-Chuan Zhan, Ziwei Liu

CoRR, 2023

The Capacity and Robustness Trade-off: Revisiting the Channel Independent Strategy for Multivariate Time Series Forecasting.

Lu Han, Han-Jia Ye, De-Chuan Zhan

CoRR, 2023

Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need.

Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan, Ziwei Liu

CoRR, 2023

Deep Class-Incremental Learning: A Survey.

Da-Wei Zhou, Qi-Wei Wang, Zhi-Hong Qi, Han-Jia Ye, De-Chuan Zhan, Ziwei Liu

CoRR, 2023

Model Spider: Learning to Rank Pre-Trained Models Efficiently.

Yi-Kai Zhang, Ting-Ji Huang, Yao-Xiang Ding, De-Chuan Zhan, Han-Jia Ye

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Beyond probability partitions: Calibrating neural networks with semantic aware grouping.

Jia-Qi Yang, De-Chuan Zhan, Le Gan

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration.

Qi-Wei Wang, Da-Wei Zhou, Yi-Kai Zhang, De-Chuan Zhan, Han-Jia Ye

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Multi-task Method for Immunofixation Electrophoresis Image Classification.

Yi Shi, Rui-Xiang Li, Wen-Qi Shao, Xin-Cen Duan, Han-Jia Ye, De-Chuan Zhan, Bai-Shen Pan, Bei-Li Wang, Wei Guo, Yuan Jiang

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

IDToolkit: A Toolkit for Benchmarking and Developing Inverse Design Algorithms in Nanophotonics.

Jia-Qi Yang, Yucheng Xu, Jia-Lei Shen, Ke-Bin Fan, De-Chuan Zhan, Yang Yang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

SeMAIL: Eliminating Distractors in Visual Imitation via Separated Models.

Shenghua Wan, Yucen Wang, Minghao Shao, Ruying Chen, De-Chuan Zhan

Proceedings of the International Conference on Machine Learning, 2023

Preserving Locality in Vision Transformers for Class Incremental Learning.

Bowen Zheng, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan

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

Improved Dynamic Spatial-Temporal Attention Network for Early Anticipation of Traffic Accidents.

Chao Yi, Ting-Ji Huang, Han-Jia Ye, De-Chuan Zhan

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

One Important Thing To Do Before Federated Training.

Yichu Xu, Wenqian Li, Yinchuan Li, Yunfeng Shao, Yan Pang, De-Chuan Zhan

Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion.

Fu-Yun Wang, Da-Wei Zhou, Liu Liu, Han-Jia Ye, Yatao Bian, De-Chuan Zhan, Peilin Zhao

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Augmentation Component Analysis: Modeling Similarity via the Augmentation Overlaps.

Lu Han, Han-Jia Ye, De-Chuan Zhan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning.

Da-Wei Zhou, Qi-Wei Wang, Han-Jia Ye, De-Chuan Zhan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning Debiased Representations via Conditional Attribute Interpolation.

Yi-Kai Zhang, Qi-Wei Wang, De-Chuan Zhan, Han-Jia Ye

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Self-Motivated Multi-Agent Exploration.

Shaowei Zhang, Jiahan Cao, Lei Yuan, Yang Yu, De-Chuan Zhan

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

Change Point Detection via Synthetic Signals.

Ting-Ji Huang, Qi-Le Zhou, Han-Jia Ye, De-Chuan Zhan

Proceedings of the Advanced Analytics and Learning on Temporal Data, 2023

2022

Learning to Classify With Incremental New Class.

Da-Wei Zhou, Yang Yang, De-Chuan Zhan

IEEE Trans. Neural Networks Learn. Syst., 2022

On Pseudo-Labeling for Class-Mismatch Semi-Supervised Learning.

Lu Han, Han-Jia Ye, De-Chuan Zhan

Trans. Mach. Learn. Res., 2022

Contrastive Principal Component Learning: Modeling Similarity by Augmentation Overlap.

Lu Han, Han-Jia Ye, De-Chuan Zhan

CoRR, 2022

Faculty Distillation with Optimal Transport.

Su Lu, Han-Jia Ye, De-Chuan Zhan

CoRR, 2022

Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks.

Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan

CoRR, 2022

Federated Learning with Position-Aware Neurons.

Xin-Chun Li, Yi-Chu Xu, Shaoming Song, Bingshuai Li, Yinchuan Li, Yunfeng Shao, De-Chuan Zhan

CoRR, 2022

Asymmetric Temperature Scaling Makes Larger Networks Teach Well Again.

Xin-Chun Li, Wen-Shu Fan, Shaoming Song, Yinchuan Li, Bingshuai Li, Yunfeng Shao, De-Chuan Zhan

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Generalized Delayed Feedback Model with Post-Click Information in Recommender Systems.

Jia-Qi Yang, De-Chuan Zhan

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Streaming Hierarchical Clustering Based on Point-Set Kernel.

Xin Han, Ye Zhu, Kai Ming Ting, De-Chuan Zhan, Gang Li

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Audio-Visual Generalized Few-Shot Learning with Prototype-Based Co-Adaptation.

Yi-Kai Zhang, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan

Proceedings of the Interspeech 2022, 2022

Avoid Overfitting User Specific Information in Federated Keyword Spotting.

Xin-Chun Li, Jin-Lin Tang, Shaoming Song, Bingshuai Li, Yinchuan Li, Yunfeng Shao, Le Gan, De-Chuan Zhan

Proceedings of the Interspeech 2022, 2022

Exploring Transferability Measures and Domain Selection in Cross-Domain Slot Filling.

Xin-Chun Li, Yan-Jia Wang, Le Gan, De-Chuan Zhan

Proceedings of the IEEE International Conference on Acoustics, 2022

FOSTER: Feature Boosting and Compression for Class-Incremental Learning.

Fu-Yun Wang, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan

Proceedings of the Computer Vision - ECCV 2022, 2022

Identifying Ambiguous Similarity Conditions via Semantic Matching.

Han-Jia Ye, Yi Shi, De-Chuan Zhan

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

Federated Learning with Position-Aware Neurons.

Xin-Chun Li, Yichu Xu, Shaoming Song, Bingshuai Li, Yinchuan Li, Yunfeng Shao, De-Chuan Zhan

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

Forward Compatible Few-Shot Class-Incremental Learning.

Da-Wei Zhou, Fu-Yun Wang, Han-Jia Ye, Liang Ma, Shiliang Pu, De-Chuan Zhan

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

RID-Noise: Towards Robust Inverse Design under Noisy Environments.

Jia-Qi Yang, Ke-Bin Fan, Hao Ma, De-Chuan Zhan

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Semi-Supervised Multi-Modal Clustering and Classification with Incomplete Modalities.

Yang Yang, De-Chuan Zhan, Yi-Feng Wu, Zhi-Bin Liu, Hui Xiong, Yuan Jiang

IEEE Trans. Knowl. Data Eng., 2021

Semi-Supervised Multi-Modal Multi-Instance Multi-Label Deep Network with Optimal Transport.

Yang Yang, Zhao-Yang Fu, De-Chuan Zhan, Zhi-Bin Liu, Yuan Jiang

IEEE Trans. Knowl. Data Eng., 2021

Heterogeneous Few-Shot Model Rectification With Semantic Mapping.

Han-Jia Ye, De-Chuan Zhan, Yuan Jiang, Zhi-Hua Zhou

IEEE Trans. Pattern Anal. Mach. Intell., 2021

Learning Adaptive Classifiers Synthesis for Generalized Few-Shot Learning.

Han-Jia Ye, Hexiang Hu, De-Chuan Zhan

Int. J. Comput. Vis., 2021

LINDA: Multi-Agent Local Information Decomposition for Awareness of Teammates.

Jiahan Cao, Lei Yuan, Jianhao Wang, Shaowei Zhang, Chongjie Zhang, Yang Yu, De-Chuan Zhan

CoRR, 2021

Preliminary Steps Towards Federated Sentiment Classification.

Xin-Chun Li, De-Chuan Zhan, Yunfeng Shao, Bingshuai Li, Shaoming Song

CoRR, 2021

Aggregate or Not? Exploring Where to Privatize in DNN Based Federated Learning Under Different Non-IID Scenes.

Xin-Chun Li, Le Gan, De-Chuan Zhan, Yunfeng Shao, Bingshuai Li, Shaoming Song

CoRR, 2021

Contextualizing Multiple Tasks via Learning to Decompose.

Han-Jia Ye, Da-Wei Zhou, Lanqing Hong, Zhenguo Li, Xiu-Shen Wei, De-Chuan Zhan

CoRR, 2021

Few-Shot Action Recognition with Compromised Metric via Optimal Transport.

Su Lu, Han-Jia Ye, De-Chuan Zhan

CoRR, 2021

Support-Target Protocol for Meta-Learning.

Su Lu, Han-Jia Ye, De-Chuan Zhan

CoRR, 2021

Deep multiple instance selection.

Xin-Chun Li, De-Chuan Zhan, Jia-Qi Yang, Yi Shi

Sci. China Inf. Sci., 2021

FedPHP: Federated Personalization with Inherited Private Models.

Xin-Chun Li, De-Chuan Zhan, Yunfeng Shao, Bingshuai Li, Shaoming Song

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Detecting Sequentially Novel Classes with Stable Generalization Ability.

Da-Wei Zhou, Yang Yang, De-Chuan Zhan

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

Towards Enabling Meta-Learning from Target Models.

Su Lu, Han-Jia Ye, Le Gan, De-Chuan Zhan

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Co-Transport for Class-Incremental Learning.

Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

FedRS: Federated Learning with Restricted Softmax for Label Distribution Non-IID Data.

Xin-Chun Li, De-Chuan Zhan

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Multi-Modal Multi-Instance Multi-Label Learning with Graph Convolutional Network.

Cheng Hang, Wei Wang, De-Chuan Zhan

Proceedings of the International Joint Conference on Neural Networks, 2021

Rethinking Label-Wise Cross-Modal Retrieval from A Semantic Sharing Perspective.

Yang Yang, Chubing Zhang, Yi-Chu Xu, Dianhai Yu, De-Chuan Zhan, Jian Yang

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Procrustean Training for Imbalanced Deep Learning.

Han-Jia Ye, De-Chuan Zhan, Wei-Lun Chao

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

Learning Placeholders for Open-Set Recognition.

Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Task Cooperation for Semi-Supervised Few-Shot Learning.

Han-Jia Ye, Xin-Chun Li, De-Chuan Zhan

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

Capturing Delayed Feedback in Conversion Rate Prediction via Elapsed-Time Sampling.

Jia-Qi Yang, Xiang Li, Shuguang Han, Tao Zhuang, De-Chuan Zhan, Xiaoyi Zeng, Bin Tong

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

Tailoring Embedding Function to Heterogeneous Few-Shot Tasks by Global and Local Feature Adaptors.

Su Lu, Han-Jia Ye, De-Chuan Zhan

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

2020

Learning Multiple Local Metrics: Global Consideration Helps.

Han-Jia Ye, De-Chuan Zhan, Nan Li, Yuan Jiang

IEEE Trans. Pattern Anal. Mach. Intell., 2020

Few-shot learning with adaptively initialized task optimizer: a practical meta-learning approach.

Han-Jia Ye, Xiang-Rong Sheng, De-Chuan Zhan

Mach. Learn., 2020

Revisiting Unsupervised Meta-Learning: Amplifying or Compensating for the Characteristics of Few-Shot Tasks.

Han-Jia Ye, Lu Han, De-Chuan Zhan

CoRR, 2020

Revisiting Meta-Learning as Supervised Learning.

Wei-Lun Chao, Han-Jia Ye, De-Chuan Zhan, Mark E. Campbell, Kilian Q. Weinberger

CoRR, 2020

Identifying and Compensating for Feature Deviation in Imbalanced Deep Learning.

Han-Jia Ye, Hong-You Chen, De-Chuan Zhan, Wei-Lun Chao

CoRR, 2020

A semi-supervised attention model for identifying authentic sneakers.

Yang Yang, Nengjun Zhu, Yi-Feng Wu, Jian Cao, De-Chuan Zhan, Hui Xiong

Big Data Min. Anal., 2020

Bottom-Up and Top-Down Graph Pooling.

Jia-Qi Yang, De-Chuan Zhan, Xin-Chun Li

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020

Towards Understanding Transfer Learning Algorithms Using Meta Transfer Features.

Xin-Chun Li, De-Chuan Zhan, Jia-Qi Yang, Yi Shi, Cheng Hang, Yi Lu

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020

Distilling Cross-Task Knowledge via Relationship Matching.

Han-Jia Ye, Su Lu, De-Chuan Zhan

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Few-Shot Learning via Embedding Adaptation With Set-to-Set Functions.

Han-Jia Ye, Hexiang Hu, De-Chuan Zhan, Fei Sha

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

What Makes Objects Similar: A Unified Multi-Metric Learning Approach.

Han-Jia Ye, De-Chuan Zhan, Yuan Jiang, Zhi-Hua Zhou

IEEE Trans. Pattern Anal. Mach. Intell., 2019

Fast generalization rates for distance metric learning.

Han-Jia Ye, De-Chuan Zhan, Yuan Jiang

Mach. Learn., 2019

Learning Classifier Synthesis for Generalized Few-Shot Learning.

Han-Jia Ye, Hexiang Hu, De-Chuan Zhan, Fei Sha

CoRR, 2019

Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability.

Yang Yang, Da-Wei Zhou, De-Chuan Zhan, Hui Xiong, Yuan Jiang

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Comprehensive Semi-Supervised Multi-Modal Learning.

Yang Yang, Ke-Tao Wang, De-Chuan Zhan, Hui Xiong, Yuan Jiang

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Automatic Successive Reinforcement Learning with Multiple Auxiliary Rewards.

Zhao-Yang Fu, De-Chuan Zhan, Xin-Chun Li, Yi-Xing Lu

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Deep Robust Unsupervised Multi-Modal Network.

Yang Yang, Yi-Feng Wu, De-Chuan Zhan, Zhi-Bin Liu, Yuan Jiang

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Multi-View Anomaly Detection: Neighborhood in Locality Matters.

Xiang-Rong Sheng, De-Chuan Zhan, Su Lu, Yuan Jiang

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Learning Embedding Adaptation for Few-Shot Learning.

Han-Jia Ye, Hexiang Hu, De-Chuan Zhan, Fei Sha

CoRR, 2018

Deep Multi-modal Learning with Cascade Consensus.

Yang Yang, Yi-Feng Wu, De-Chuan Zhan, Yuan Jiang

Proceedings of the PRICAI 2018: Trends in Artificial Intelligence, 2018

Multi-network User Identification via Graph-Aware Embedding.

Yang Yang, De-Chuan Zhan, Yi-Feng Wu, Yuan Jiang

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Complex Object Classification: A Multi-Modal Multi-Instance Multi-Label Deep Network with Optimal Transport.

Yang Yang, Yi-Feng Wu, De-Chuan Zhan, Zhi-Bin Liu, Yuan Jiang

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Distance Metric Facilitated Transportation between Heterogeneous Domains.

Han-Jia Ye, Xiang-Rong Sheng, De-Chuan Zhan, Peng He

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Semi-Supervised Multi-Modal Learning with Incomplete Modalities.

Yang Yang, De-Chuan Zhan, Xiang-Rong Sheng, Yuan Jiang

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Rectify Heterogeneous Models with Semantic Mapping.

Han-Jia Ye, De-Chuan Zhan, Yuan Jiang, Zhi-Hua Zhou

Proceedings of the 35th International Conference on Machine Learning, 2018

Learning Semantic Features for Software Defect Prediction by Code Comments Embedding.

Xuan Huo, Yang Yang, Ming Li, De-Chuan Zhan

Proceedings of the IEEE International Conference on Data Mining, 2018

DMTMV: A Unified Learning Framework for Deep Multi-task Multi-view Learning.

Yi-Feng Wu, De-Chuan Zhan, Yuan Jiang

Proceedings of the 2018 IEEE International Conference on Big Knowledge, 2018

2017

Learning Mahalanobis Distance Metric: Considering Instance Disturbance Helps.

Han-Jia Ye, De-Chuan Zhan, Xue-Min Si, Yuan Jiang

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Modal Consistency based Pre-Trained Multi-Model Reuse.

Yang Yang, De-Chuan Zhan, Xiang-Yu Guo, Yuan Jiang

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Instance Specific Discriminative Modal Pursuit: A Serialized Approach.

Yang Yang, De-Chuan Zhan, Ying Fan, Yuan Jiang

Proceedings of The 9th Asian Conference on Machine Learning, 2017

Deep Learning for Fixed Model Reuse.

Yang Yang, De-Chuan Zhan, Ying Fan, Yuan Jiang, Zhi-Hua Zhou

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

What Makes Objects Similar: A Unified Multi-Metric Learning Approach.

Han-Jia Ye, De-Chuan Zhan, Xue-Min Si, Yuan Jiang, Zhi-Hua Zhou

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Learning by Actively Querying Strong Modal Features.

Yang Yang, De-Chuan Zhan, Yuan Jiang

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

College Student Scholarships and Subsidies Granting: A Multi-modal Multi-label Approach.

Han-Jia Ye, De-Chuan Zhan, Xiaolin Li, Zhen-Chuan Huang, Yuan Jiang

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Learning Feature Aware Metric.

Han-Jia Ye, De-Chuan Zhan, Xue-Min Si, Yuan Jiang

Proceedings of The 8th Asian Conference on Machine Learning, 2016

Learning Expected Hitting Time Distance.

De-Chuan Zhan, Peng Hu, Zui Chu, Zhi-Hua Zhou

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Instance Specific Metric Subspace Learning: A Bayesian Approach.

Han-Jia Ye, De-Chuan Zhan, Yuan Jiang

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Pairwised Specific Distance Learning from Physical Linkages.

Ju-Hua Hu, De-Chuan Zhan, Xintao Wu, Yuan Jiang, Zhi-Hua Zhou

ACM Trans. Knowl. Discov. Data, 2015

Auxiliary Information Regularized Machine for Multiple Modality Feature Learning.

Yang Yang, Han-Jia Ye, De-Chuan Zhan, Yuan Jiang

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Rank Consistency based Multi-View Learning: A Privacy-Preserving Approach.

Han-Jia Ye, De-Chuan Zhan, Yuan Miao, Yuan Jiang, Zhi-Hua Zhou

Proceedings of the 24th ACM International Conference on Information and Knowledge Management, 2015

2014

A Novel Serial Multimodal Biometrics Framework Based on Semisupervised Learning Techniques.

Qing Zhang, Yilong Yin, De-Chuan Zhan, Jingliang Peng

IEEE Trans. Inf. Forensics Secur., 2014

2013

Multi Gesture Recognition: A Tracking Learning Detection Approach.

Meng-Yuan Shi, De-Chuan Zhan

Proceedings of the Intelligence Science and Big Data Engineering, 2013

Multi-Modal Image Annotation with Multi-Instance Multi-Label LDA.

Cam-Tu Nguyen, De-Chuan Zhan, Zhi-Hua Zhou

Proceedings of the IJCAI 2013, 2013

2012

Learning with Weak Views Based on Dependence Maximization Dimensionality Reduction.

Qing Zhang, De-Chuan Zhan, Yilong Yin

Proceedings of the Intelligent Science and Intelligent Data Engineering, 2012

2009

Learning instance specific distances using metric propagation.

De-Chuan Zhan, Ming Li, Yu-Feng Li, Zhi-Hua Zhou

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2007

Predicting Future Customers via Ensembling Gradually Expanded Trees.

Yang Yu, De-Chuan Zhan, Xu-Ying Liu, Ming Li, Zhi-Hua Zhou

Int. J. Data Warehous. Min., 2007

Semi-Supervised Learning with Very Few Labeled Training Examples.

Zhi-Hua Zhou, De-Chuan Zhan, Qiang Yang

Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006

Neighbor Line-Based Locally Linear Embedding.

De-Chuan Zhan, Zhi-Hua Zhou

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2006

2005

Supervised nonlinear dimensionality reduction for visualization and classification.

Xin Geng, De-Chuan Zhan, Zhi-Hua Zhou

IEEE Trans. Syst. Man Cybern. Part B, 2005