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ORCIDYuan Jiang 0001
Person information
- affiliation: Nanjing University, National Key Laboratory for Novel Software Technology, China
Other persons with the same name
- Yuan Jiang — disambiguation page
- Yuan Jiang 0002
![[0000-0002-1863-404X]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-1863-404X")
— Shanghai University, School of Communication and Information Engineering, Key Laboratory of Specialty Fiber Optics and Optical Access Networks, China - Yuan Jiang 0003 — Beijing Institute of Technology, School of Information and Electronics, Radar Research Lab, China
- Yuan Jiang 0004 — Southwest University, College of Computer and Information Science, Chongqing, China
- Yuan Jiang 0005 — Beihang University, School of Automation Science and Electrical Engineering, Beijing, China
- Yuan Jiang 0006 — iFLYTEK Co., Ltd., Hefei, China (and 1 more)
- Yuan Jiang 0007 — Nanyang Technological University, Singapore
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Journal Articles
- 2024
[j28]Peng Tan, Zhi-Hao Tan, Yuan Jiang, Zhi-Hua Zhou:
Towards enabling learnware to handle heterogeneous feature spaces. Mach. Learn. 113(4): 1839-1860 (2024)- [j27]Jin-Hui Wu, Shao-Qun Zhang, Yuan Jiang, Zhi-Hua Zhou:
Theoretical Exploration of Flexible Transmitter Model. IEEE Trans. Neural Networks Learn. Syst. 35(3): 3674-3688 (2024) - 2023
- [j26]Yang Yang, Da-Wei Zhou, De-Chuan Zhan, Hui Xiong, Yuan Jiang, Jian Yang:
Cost-Effective Incremental Deep Model: Matching Model Capacity With the Least Sampling. IEEE Trans. Knowl. Data Eng. 35(4): 3575-3588 (2023) - [j25]Han Wang, Yang Yu, Yuan Jiang:
Fully Decentralized Multiagent Communication via Causal Inference. IEEE Trans. Neural Networks Learn. Syst. 34(12): 10193-10202 (2023) - 2022
- [j24]Zhen-Yu Zhang, Peng Zhao, Yuan Jiang, Zhi-Hua Zhou:
Learning From Incomplete and Inaccurate Supervision. IEEE Trans. Knowl. Data Eng. 34(12): 5854-5868 (2022) - 2021
- [j23]Jia-Lue Chen, Jia-Jia Cai, Yuan Jiang, Sheng-Jun Huang:
PU Active Learning for Recommender Systems. Neural Process. Lett. 53(5): 3639-3652 (2021) - [j22]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) - [j21]Yang Yang, De-Chuan Zhan, Yi-Feng Wu, Zhi-Bin Liu, Hui Xiong, Yuan Jiang:
Semi-Supervised Multi-Modal Clustering and Classification with Incomplete Modalities. IEEE Trans. Knowl. Data Eng. 33(2): 682-695 (2021) - [j20]Yang Yang, Zhao-Yang Fu, De-Chuan Zhan, Zhi-Bin Liu, Yuan Jiang:
Semi-Supervised Multi-Modal Multi-Instance Multi-Label Deep Network with Optimal Transport. IEEE Trans. Knowl. Data Eng. 33(2): 696-709 (2021) - 2020
- [j19]Zhi-Hao Tan, Peng Tan, Yuan Jiang, Zhi-Hua Zhou:
Multi-label optimal margin distribution machine. Mach. Learn. 109(3): 623-642 (2020) - [j18]Lu Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Yuan Jiang:
Spanning attack: reinforce black-box attacks with unlabeled data. Mach. Learn. 109(12): 2349-2368 (2020) - [j17]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) - 2019
- [j16]Han-Jia Ye, De-Chuan Zhan, Yuan Jiang:
Fast generalization rates for distance metric learning. Mach. Learn. 108(2): 267-295 (2019) - [j15]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) - [j14]Shao-Yuan Li, Yuan Jiang, Nitesh V. Chawla, Zhi-Hua Zhou:
Multi-Label Learning from Crowds. IEEE Trans. Knowl. Data Eng. 31(7): 1369-1382 (2019) - 2017
- [j13]Shaowu Liu, Gang Li, Truyen Tran, Yuan Jiang:
Preference Relation-based Markov Random Fields for Recommender Systems. Mach. Learn. 106(4): 523-546 (2017) - [j12]Shaowu Liu, Gang Li, Truyen Tran, Yuan Jiang:
Erratum to: Preference Relation-based Markov Random Fields for Recommender Systems. Mach. Learn. 106(4): 547 (2017) - 2015
- [j11]Ju-Hua Hu, De-Chuan Zhan, Xintao Wu, Yuan Jiang, Zhi-Hua Zhou:
Pairwised Specific Distance Learning from Physical Linkages. ACM Trans. Knowl. Discov. Data 9(3): 20:1-20:27 (2015) - 2012
- [j10]Lei Yuan, Alexander Woodard, Shuiwang Ji, Yuan Jiang, Zhi-Hua Zhou, Sudhir Kumar, Jieping Ye:
Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval. BMC Bioinform. 13: 107 (2012) - 2011
- [j9]Yuan Jiang, Ming Li, Zhi-Hua Zhou:
Software Defect Detection with Rocus. J. Comput. Sci. Technol. 26(2): 328-342 (2011) - [j8]Yong Wang, Yuan Jiang, Yi Wu, Zhi-Hua Zhou:
Spectral Clustering on Multiple Manifolds. IEEE Trans. Neural Networks 22(7): 1149-1161 (2011) - 2009
- [j7]Yuan Jiang, Ming Li, Zhi-Hua Zhou:
Mining extremely small data sets with application to software reuse. Softw. Pract. Exp. 39(4): 423-440 (2009) - 2004
- [j6]Yuan Jiang, Zhi-Hua Zhou:
SOM Ensemble-Based Image Segmentation. Neural Process. Lett. 20(3): 171-178 (2004) - [j5]Zhi-Hua Zhou, Yuan Jiang:
NeC4.5: Neural Ensemble Based C4.5. IEEE Trans. Knowl. Data Eng. 16(6): 770-773 (2004) - 2003
- [j4]Zhi-Hua Zhou, Yuan Jiang, Shifu Chen:
Extracting symbolic rules from trained neural network ensembles. AI Commun. 16(1): 3-15 (2003) - [j3]Zhi-Hua Zhou, Yuan Jiang:
Medical diagnosis with C4.5 rule preceded by artificial neural network ensemble. IEEE Trans. Inf. Technol. Biomed. 7(1): 37-42 (2003) - 2002
- [j2]Zhi-Hua Zhou, Yuan Jiang, Yu-Bin Yang, Shifu Chen:
Lung cancer cell identification based on artificial neural network ensembles. Artif. Intell. Medicine 24(1): 25-36 (2002) - 2000
- [j1]Zhi-Hua Zhou, Yuan Jiang, Shifu Chen:
A general neural framework for classification rule mining. Int. J. Comput. Syst. Signals 1(2): 154-168 (2000)
Conference and Workshop Papers
- 2024
- [c78]Xiao-Dong Bi, Shao-Qun Zhang, Yuan Jiang:
MEPSI: An MDL-Based Ensemble Pruning Approach with Structural Information. AAAI 2024: 11078-11086 - [c77]Lue Tao, Yu-Xuan Huang, Wang-Zhou Dai, Yuan Jiang:
Deciphering Raw Data in Neuro-Symbolic Learning with Provable Guarantees. AAAI 2024: 15310-15318 - [c76]Jun-Peng Jiang, Han-Jia Ye, Leye Wang, Yang Yang, Yuan Jiang, De-Chuan Zhan:
Tabular Insights, Visual Impacts: Transferring Expertise from Tables to Images. ICML 2024 - 2023
- [c75]Yu-Xuan Huang, Wang-Zhou Dai, Yuan Jiang, Zhi-Hua Zhou:
Enabling Knowledge Refinement upon New Concepts in Abductive Learning. AAAI 2023: 7928-7935 - [c74]Qin-Cheng Zheng, Shen-Huan Lyu, Shao-Qun Zhang, Yuan Jiang, Zhi-Hua Zhou:
On the Consistency Rate of Decision Tree Learning Algorithms. AISTATS 2023: 7824-7848 - [c73]Yi Xie, Zhi-Hao Tan, Yuan Jiang, Zhi-Hua Zhou:
Identifying Helpful Learnwares Without Examining the Whole Market. ECAI 2023: 2752-2759 - [c72]Xin-Qiang Cai, Yao-Xiang Ding, Zi-Xuan Chen, Yuan Jiang, Masashi Sugiyama, Zhi-Hua Zhou:
Seeing Differently, Acting Similarly: Heterogeneously Observable Imitation Learning. ICLR 2023 - [c71]Yu-Xuan Huang, Zequn Sun, Guangyao Li, Xiaobin Tian, Wang-Zhou Dai, Wei Hu, Yuan Jiang, Zhi-Hua Zhou:
Enabling Abductive Learning to Exploit Knowledge Graph. IJCAI 2023: 3839-3847 - [c70]Peng Tan, Zhi-Hao Tan, Yuan Jiang, Zhi-Hua Zhou:
Handling Learnwares Developed from Heterogeneous Feature Spaces without Auxiliary Data. IJCAI 2023: 4235-4243 - [c69]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:
A Multi-task Method for Immunofixation Electrophoresis Image Classification. MICCAI (6) 2023: 148-158 - [c68]Jin-Hui Wu, Shao-Qun Zhang, Yuan Jiang, Zhi-Hua Zhou:
Complex-valued Neurons Can Learn More but Slower than Real-valued Neurons via Gradient Descent. NeurIPS 2023 - [c67]Jun-Peng Jiang, Han-Jia Ye, Leye Wang, Yang Yang, Yuan Jiang, De-Chuan Zhan:
On Transferring Expert Knowledge from Tabular Data to Images. UniReps 2023: 102-115 - 2022
- [c66]Zi-Xuan Chen, Xin-Qiang Cai, Yuan Jiang, Zhi-Hua Zhou:
Anomaly Guided Policy Learning from Imperfect Demonstrations. AAMAS 2022: 244-252 - [c65]Zhen-Yu Zhang, Yuyang Qian, Yu-Jie Zhang, Yuan Jiang, Zhi-Hua Zhou:
Adaptive Learning for Weakly Labeled Streams. KDD 2022: 2556-2564 - [c64]Zhi-Hao Tan, Yi Xie, Yuan Jiang, Zhi-Hua Zhou:
Real-Valued Backpropagation is Unsuitable for Complex-Valued Neural Networks. NeurIPS 2022 - 2021
- [c63]Bi-Cun Xu, Kai Ming Ting, Yuan Jiang:
Isolation Graph Kernel. AAAI 2021: 10487-10495 - [c62]Xin-Qiang Cai, Yao-Xiang Ding, Yuan Jiang, Zhi-Hua Zhou:
Imitation Learning from Pixel-Level Demonstrations by HashReward. AAMAS 2021: 279-287 - [c61]Yi-He Chen, Shen-Huan Lyu, Yuan Jiang:
Improving Deep Forest by Exploiting High-order Interactions. ICDM 2021: 1030-1035 - [c60]Zhao-Yu Zhang, Shao-Qun Zhang, Yuan Jiang, Zhi-Hua Zhou:
LIFE: Learning Individual Features for Multivariate Time Series Prediction with Missing Values. ICDM 2021: 1511-1516 - [c59]Le-Wen Cai, Wang-Zhou Dai, Yu-Xuan Huang, Yufeng Li, Stephen H. Muggleton, Yuan Jiang:
Abductive Learning with Ground Knowledge Base. IJCAI 2021: 1815-1821 - [c58]Yu-Xuan Huang, Wang-Zhou Dai, Le-Wen Cai, Stephen H. Muggleton, Yuan Jiang:
Fast Abductive Learning by Similarity-based Consistency Optimization. NeurIPS 2021: 26574-26584 - [c57]Yi-Xuan Xu, Ming Pang, Ji Feng, Kai Ming Ting, Yuan Jiang, Zhi-Hua Zhou:
Reconstruction-based Anomaly Detection with Completely Random Forest. SDM 2021: 127-135 - 2020
- [c56]Peng Zhao, Lijun Zhang, Yuan Jiang, Zhi-Hua Zhou:
A Simple Approach for Non-stationary Linear Bandits. AISTATS 2020: 746-755 - [c55]Liang Yang, Xi-Zhu Wu, Yuan Jiang, Zhi-Hua Zhou:
Multi-Label Learning with Deep Forest. ECAI 2020: 1634-1641 - [c54]Lan-Zhe Guo, Zhenyu Zhang, Yuan Jiang, Yufeng Li, Zhi-Hua Zhou:
Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data. ICML 2020: 3897-3906 - [c53]Zhenyu Zhang, Peng Zhao, Yuan Jiang, Zhi-Hua Zhou:
Learning with Feature and Distribution Evolvable Streams. ICML 2020: 11317-11327 - [c52]Lu Wang, Xuanqing Liu, Jinfeng Yi, Yuan Jiang, Cho-Jui Hsieh:
Provably Robust Metric Learning. NeurIPS 2020 - 2019
- [c51]Xiang-Rong Sheng, De-Chuan Zhan, Su Lu, Yuan Jiang:
Multi-View Anomaly Detection: Neighborhood in Locality Matters. AAAI 2019: 4894-4901 - [c50]Yang Yang, Yi-Feng Wu, De-Chuan Zhan, Zhi-Bin Liu, Yuan Jiang:
Deep Robust Unsupervised Multi-Modal Network. AAAI 2019: 5652-5659 - [c49]Xin-Qiang Cai, Peng Zhao, Kai-Ming Ting, Xin Mu, Yuan Jiang:
Nearest Neighbor Ensembles: An Effective Method for Difficult Problems in Streaming Classification with Emerging New Classes. ICDM 2019: 970-975 - [c48]Yang Yang, Ke-Tao Wang, De-Chuan Zhan, Hui Xiong, Yuan Jiang:
Comprehensive Semi-Supervised Multi-Modal Learning. IJCAI 2019: 4092-4098 - [c47]Yang Yang, Da-Wei Zhou, De-Chuan Zhan, Hui Xiong, Yuan Jiang:
Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability. KDD 2019: 74-82 - [c46]Zhenyu Zhang, Peng Zhao, Yuan Jiang, Zhi-Hua Zhou:
Learning from Incomplete and Inaccurate Supervision. KDD 2019: 1017-1025 - 2018
- [c45]Chong Liu, Peng Zhao, Sheng-Jun Huang, Yuan Jiang, Zhi-Hua Zhou:
Dual Set Multi-Label Learning. AAAI 2018: 3635-3642 - [c44]Yi-Feng Wu, De-Chuan Zhan, Yuan Jiang:
DMTMV: A Unified Learning Framework for Deep Multi-task Multi-view Learning. ICBK 2018: 49-56 - [c43]Han-Jia Ye, De-Chuan Zhan, Yuan Jiang, Zhi-Hua Zhou:
Rectify Heterogeneous Models with Semantic Mapping. ICML 2018: 1904-1913 - [c42]Yang Yang, De-Chuan Zhan, Xiang-Rong Sheng, Yuan Jiang:
Semi-Supervised Multi-Modal Learning with Incomplete Modalities. IJCAI 2018: 2998-3004 - [c41]Yang Yang, Yi-Feng Wu, De-Chuan Zhan, Zhi-Bin Liu, Yuan Jiang:
Complex Object Classification: A Multi-Modal Multi-Instance Multi-Label Deep Network with Optimal Transport. KDD 2018: 2594-2603 - [c40]Yang Yang, De-Chuan Zhan, Yi-Feng Wu, Yuan Jiang:
Multi-network User Identification via Graph-Aware Embedding. PAKDD (2) 2018: 209-221 - [c39]Yang Yang, Yi-Feng Wu, De-Chuan Zhan, Yuan Jiang:
Deep Multi-modal Learning with Cascade Consensus. PRICAI 2018: 64-72 - [c38]Shao-Yuan Li, Yuan Jiang:
Multi-label Crowdsourcing Learning with Incomplete Annotations. PRICAI (1) 2018: 232-245 - 2017
- [c37]Yang Yang, De-Chuan Zhan, Ying Fan, Yuan Jiang, Zhi-Hua Zhou:
Deep Learning for Fixed Model Reuse. AAAI 2017: 2831-2837 - [c36]Yang Yang, De-Chuan Zhan, Ying Fan, Yuan Jiang:
Instance Specific Discriminative Modal Pursuit: A Serialized Approach. ACML 2017: 65-80 - [c35]Wei Wang, Xiang-Yu Guo, Shao-Yuan Li, Yuan Jiang, Zhi-Hua Zhou:
Obtaining High-Quality Label by Distinguishing between Easy and Hard Items in Crowdsourcing. IJCAI 2017: 2964-2970 - [c34]Yang Yang, De-Chuan Zhan, Xiang-Yu Guo, Yuan Jiang:
Modal Consistency based Pre-Trained Multi-Model Reuse. IJCAI 2017: 3287-3293 - [c33]Han-Jia Ye, De-Chuan Zhan, Xue-Min Si, Yuan Jiang:
Learning Mahalanobis Distance Metric: Considering Instance Disturbance Helps. IJCAI 2017: 3315-3321 - [c32]Yu Zhang, Yuan Jiang:
Multimodal Linear Discriminant Analysis via Structural Sparsity. IJCAI 2017: 3448-3454 - [c31]Peng Zhao, Yuan Jiang, Zhi-Hua Zhou:
Multi-View Matrix Completion for Clustering with Side Information. PAKDD (2) 2017: 403-415 - 2016
- [c30]Han-Jia Ye, De-Chuan Zhan, Yuan Jiang:
Instance Specific Metric Subspace Learning: A Bayesian Approach. AAAI 2016: 2272-2278 - [c29]Han-Jia Ye, De-Chuan Zhan, Xue-Min Si, Yuan Jiang:
Learning Feature Aware Metric. ACML 2016: 286-301 - [c28]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 - [c27]Yang Yang, De-Chuan Zhan, Yuan Jiang:
Learning by Actively Querying Strong Modal Features. IJCAI 2016: 2280-2286 - [c26]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
- [c25]Shaowu Liu, Gang Li, Truyen Tran, Yuan Jiang:
Preference Relation-based Markov Random Fields for Recommender Systems. ACML 2015: 157-172 - [c24]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 - [c23]Yang Yang, Han-Jia Ye, De-Chuan Zhan, Yuan Jiang:
Auxiliary Information Regularized Machine for Multiple Modality Feature Learning. IJCAI 2015: 1033-1039 - [c22]Nan Li, Yuan Jiang, Zhi-Hua Zhou:
Multi-label Selective Ensemble. MCS 2015: 76-88 - 2014
- [c21]Shao-Yuan Li, Yuan Jiang, Zhi-Hua Zhou:
Partial Multi-View Clustering. AAAI 2014: 1968-1974 - [c20]Yue Zhu, Jianxin Wu, Yuan Jiang, Zhi-Hua Zhou:
Learning with Augmented Multi-Instance View. ACML 2014 - 2013
- [c19]Shu-Jun Yang, Yuan Jiang, Zhi-Hua Zhou:
Multi-Instance Multi-Label Learning with Weak Label. IJCAI 2013: 1862-1868 - 2012
- [c18]Yufeng Li, Ju-Hua Hu, Yuan Jiang, Zhi-Hua Zhou:
Towards Discovering What Patterns Trigger What Labels. AAAI 2012: 1012-1018 - [c17]Quannan Li, Xinggang Wang, Wei Wang, Yuan Jiang, Zhi-Hua Zhou, Zhuowen Tu:
Disagreement-Based Multi-system Tracking. ACCV Workshops (2) 2012: 320-334 - [c16]Xin-Shun Xu, Yuan Jiang, Xiangyang Xue, Zhi-Hua Zhou:
Semi-supervised multi-instance multi-label learning for video annotation task. ACM Multimedia 2012: 737-740 - 2011
- [c15]Yong Wang, Yuan Jiang, Yi Wu, Zhi-Hua Zhou:
Localized K-Flats. AAAI 2011: 525-530 - [c14]Yong Wang, Yuan Jiang, Yi Wu, Zhi-Hua Zhou:
Local and Structural Consistency for Multi-Manifold Clustering. IJCAI 2011: 1559-1564 - [c13]Xin-Shun Xu, Yuan Jiang, Liang Peng, Xiangyang Xue, Zhi-Hua Zhou:
Ensemble approach based on conditional random field for multi-label image and video annotation. ACM Multimedia 2011: 1377-1380 - 2010
- [c12]Yong Wang, Yuan Jiang, Yi Wu, Zhi-Hua Zhou:
Multi-manifold Clustering. PRICAI 2010: 280-291 - 2009
- [c11]Li-Ping Liu, Yuan Jiang, Zhi-Hua Zhou:
Least Square Incremental Linear Discriminant Analysis. ICDM 2009: 298-306 - [c10]Zhi-Hua Zhou, Michael K. Ng, Qiao-Qiao She, Yuan Jiang:
Budget Semi-supervised Learning. PAKDD 2009: 588-595 - 2008
- [c9]Li-Ping Liu, Yang Yu, Yuan Jiang, Zhi-Hua Zhou:
TEFE: A Time-Efficient Approach to Feature Extraction. ICDM 2008: 423-432 - 2006
- [c8]Yuan Jiang, Ming Li, Zhi-Hua Zhou:
Generation of Comprehensible Hypotheses from Gene Expression Data. BioDM 2006: 116-123 - 2005
- [c7]Zhi-Hua Zhou, Xiao-Bing Xue, Yuan Jiang:
Locating Regions of Interest in CBIR with Multi-instance Learning Techniques. Australian Conference on Artificial Intelligence 2005: 92-101 - [c6]Yuan Jiang, Jinjiang Ling, Gang Li, Honghua Dai, Zhi-Hua Zhou:
Dependency Bagging. RSFDGrC (1) 2005: 491-500 - 2004
- [c5]Zhi-Hua Zhou, Ke-Jia Chen, Yuan Jiang:
Exploiting Unlabeled Data in Content-Based Image Retrieval. ECML 2004: 525-536 - [c4]Yuan Jiang, Zhi-Hua Zhou:
Editing Training Data for kNN Classifiers with Neural Network Ensemble. ISNN (1) 2004: 356-361 - 2003
- [c3]Yuan Jiang, Kejia Chen, Zhi-Hua Zhou:
SOM Based Image Segmentation. RSFDGrC 2003: 640-643 - 2002
- [c2]Zhi-Hua Zhou, Yuan Jiang, Xu-Ri Yin, Shifu Chen:
The Application of Visualization and Neural Network Techniques in a Power Transformer Condition Monitoring System. IEA/AIE 2002: 325-334 - 2001
- [c1]Zhi-Hua Zhou, Jianxin Wu, Yuan Jiang, Shifu Chen:
Genetic Algorithm based Selective Neural Network Ensemble. IJCAI 2001: 797-802
Parts in Books or Collections
- 2020
- [p1]Ji Feng, Yi-Xuan Xu, Yong-Gang Wang, Yuan Jiang:
Federated Soft Gradient Boosting Machine for Streaming Data. Federated Learning 2020: 93-107
Informal and Other Publications
- 2023
- [i12]Yi-Xiao He, Shen-Huan Lyu, Yuan Jiang:
Interpreting Deep Forest through Feature Contribution and MDI Feature Importance. CoRR abs/2305.00805 (2023) - [i11]Lue Tao, Yu-Xuan Huang, Wang-Zhou Dai, Yuan Jiang:
Deciphering Raw Data in Neuro-Symbolic Learning with Provable Guarantees. CoRR abs/2308.10487 (2023) - 2021
- [i10]Yang Yang, Zhao-Yang Fu, De-Chuan Zhan, Zhi-Bin Liu, Yuan Jiang:
Semi-Supervised Multi-Modal Multi-Instance Multi-Label Deep Network with Optimal Transport. CoRR abs/2104.08489 (2021) - [i9]Xin-Qiang Cai, Yao-Xiang Ding, Zi-Xuan Chen, Yuan Jiang, Masashi Sugiyama, Zhi-Hua Zhou:
Seeing Differently, Acting Similarly: Imitation Learning with Heterogeneous Observations. CoRR abs/2106.09256 (2021) - [i8]Zhao-Yu Zhang, Shao-Qun Zhang, Yuan Jiang, Zhi-Hua Zhou:
LIFE: Learning Individual Features for Multivariate Time Series Prediction with Missing Values. CoRR abs/2109.14844 (2021) - [i7]Jin-Hui Wu, Shao-Qun Zhang, Yuan Jiang, Zhi-Hua Zhou:
Towards Theoretical Understanding of Flexible Transmitter Networks via Approximation and Local Minima. CoRR abs/2111.06027 (2021) - 2020
- [i6]Lu Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Yuan Jiang:
Spanning Attack: Reinforce Black-box Attacks with Unlabeled Data. CoRR abs/2005.04871 (2020) - [i5]Ji Feng, Yi-Xuan Xu, Yuan Jiang, Zhi-Hua Zhou:
Soft Gradient Boosting Machine. CoRR abs/2006.04059 (2020) - [i4]Lu Wang, Xuanqing Liu, Jinfeng Yi, Yuan Jiang, Cho-Jui Hsieh:
Provably Robust Metric Learning. CoRR abs/2006.07024 (2020) - 2019
- [i3]Xin-Qiang Cai, Yao-Xiang Ding, Yuan Jiang, Zhi-Hua Zhou:
Expert-Level Atari Imitation Learning from Demonstrations Only. CoRR abs/1909.03773 (2019) - [i2]Liang Yang, Xi-Zhu Wu, Yuan Jiang, Zhi-Hua Zhou:
Multi-Label Learning with Deep Forest. CoRR abs/1911.06557 (2019) - 2015
- [i1]Shao-Yuan Li, Yuan Jiang, Zhi-Hua Zhou:
Multi-Label Active Learning from Crowds. CoRR abs/1508.00722 (2015)
Coauthor Index
[j28] [j27] [j24] [j22] [j19] [j15] [j14] [j11] [j10] [j9] [j8] [j7] [j6] [j5] [j4] [j3] [j2] [j1] [c75] [c74] [c73] [c72] [c71] [c70] [c68] [c66] [c65] [c64] [c62] [c60] [c57] [c56] [c55] [c54] [c53] [c46] [c45] [c43] [c37] [c35] [c31] [c26] [c24] [c22] [c21] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [c9] [c8] [c7] [c6] [c5] [c4] [c3] [c2] [c1] [i9] [i8] [i7] [i5] [i3] [i2] [i1]
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