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ORCIDYufeng Li 0008
Person information
- affiliation: Nanjing University, China
Other persons with the same name
- Yufeng Li (aka: Yu-Feng Li) — disambiguation page
- Yufeng Li 0001
![[0000-0002-4731-829X]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0002-4731-829X")
— Shenyang Aerospace University, College of Electronic Information Engineering, Shenyang, China - Yufeng Li 0002 — Shanghai University, School of Computer Engineering and Science, Shanghai, China (and 1 more)
- Yufeng Li 0003 — University of Alberta, Department of Electrical and Computer Engineering, Edmonton, Canada
- Yufeng Li 0004 — Guizhou University, College of Computer Science and Technology, State Key Laboratory of Public Big Data, Guiyang, China
- Yufeng Li 0005 — Fuzhou University, School of Mechanical Engineering and Automation, Fuzhou, China
- Yufeng Li 0006 — Northwestern Polytechnical University, School of Marine Science and Technology, Xi'an, China
- Yufeng Li 0007 — Chongqing University, School of Mechanical Engineering, State Key Laboratory of Mechanical Transmission, Chongqing, China
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2020 – today
- 2025
[j17]Lan-Zhe Guo, Lin-Han Jia, Jie-Jing Shao, Yufeng Li:
Robust semi-supervised learning in open environments. Frontiers Comput. Sci. 19(8): 198345 (2025)- 2024
- [j16]Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Yufeng Li:
LAMDA-SSL: a comprehensive semi-supervised learning toolkit. Sci. China Inf. Sci. 67(1) (2024) - [j15]Zhi Zhou, Yi-Xuan Jin, Yufeng Li:
Rts: learning robustly from time series data with noisy label. Frontiers Comput. Sci. 18(6): 186332 (2024) - [j14]Weikai Yang, Yukai Guo, Jing Wu, Zheng Wang, Lan-Zhe Guo, Yufeng Li, Shixia Liu:
Interactive Reweighting for Mitigating Label Quality Issues. IEEE Trans. Vis. Comput. Graph. 30(3): 1837-1852 (2024) - [c66]Xiaowen Yang, Jie-Jing Shao, Wei-Wei Tu, Yufeng Li, Wang-Zhou Dai, Zhi-Hua Zhou:
Safe Abductive Learning in the Presence of Inaccurate Rules. AAAI 2024: 16361-16369 - [c65]Dingchu Zhang, Zhi Zhou, Yufeng Li:
Robust Test-Time Adaptation for Zero-Shot Prompt Tuning. AAAI 2024: 16714-16722 - [c64]Heng-Kai Zhang, Yi-Ge Zhang, Zhi Zhou, Yufeng Li:
HONGAT: Graph Attention Networks in the Presence of High-Order Neighbors. AAAI 2024: 16750-16758 - [c63]Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Yufeng Li:
Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments. ICLR 2024 - [c62]Zhi Zhou, Ming Yang, Jiang-Xin Shi, Lan-Zhe Guo, Yufeng Li:
DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection. ICML 2024 - [c61]Jiang-Xin Shi, Tong Wei, Zhi Zhou, Jie-Jing Shao, Xin-Yan Han, Yufeng Li:
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts. ICML 2024 - [c60]Xiaowen Yang, Wenda Wei, Jie-Jing Shao, Yufeng Li, Zhi-Hua Zhou:
Analysis for Abductive Learning and Neural-Symbolic Reasoning Shortcuts. ICML 2024 - [c59]Heng-Kai Zhang, Yi-Ge Zhang, Zhi Zhou, Yufeng Li:
LSPAN: Spectrally Localized Augmentation for Graph Consistency Learning. IJCAI 2024: 5462-5470 - [c58]Jiang-Xin Shi, Chi Zhang, Tong Wei, Yufeng Li:
Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model. KDD 2024: 2663-2673 - [i23]Zhi Zhou, Jiang-Xin Shi, Peng-Xiao Song, Xiaowen Yang, Yi-Xuan Jin, Lan-Zhe Guo, Yufeng Li:
LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model. CoRR abs/2406.04614 (2024) - [i22]Shi-Yu Tian, Zhi Zhou, Lin-Han Jia, Lan-Zhe Guo, Yufeng Li:
Robustness Assessment of Mathematical Reasoning in the Presence of Missing and Contradictory Conditions. CoRR abs/2406.05055 (2024) - [i21]Jiang-Xin Shi, Chi Zhang, Tong Wei, Yufeng Li:
Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model. CoRR abs/2406.12638 (2024) - [i20]Zhi Zhou, Lan-Zhe Guo, Peng-Xiao Song, Yufeng Li:
You Only Submit One Image to Find the Most Suitable Generative Model. CoRR abs/2412.12232 (2024) - 2023
- [c57]Lan-Zhe Guo, Zhi Zhou, Yufeng Li, Zhi-Hua Zhou:
Identifying Useful Learnwares for Heterogeneous Label Spaces. ICML 2023: 12122-12131 - [c56]Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Jie-Jing Shao, Yuke Xiang, Yufeng Li:
Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions. ICML 2023: 14886-14901 - [c55]Zhi Zhou, Lan-Zhe Guo, Lin-Han Jia, Dingchu Zhang, Yufeng Li:
ODS: Test-Time Adaptation in the Presence of Open-World Data Shift. ICML 2023: 42574-42588 - [c54]Jiang-Xin Shi, Tong Wei, Yuke Xiang, Yufeng Li:
How Re-sampling Helps for Long-Tail Learning? NeurIPS 2023 - [i19]Jiang-Xin Shi, Tong Wei, Zhi Zhou, Xin-Yan Han, Jie-Jing Shao, Yufeng Li:
Parameter-Efficient Long-Tailed Recognition. CoRR abs/2309.10019 (2023) - [i18]Jie-Jing Shao, Jiang-Xin Shi, Xiaowen Yang, Lan-Zhe Guo, Yufeng Li:
Investigating the Limitation of CLIP Models: The Worst-Performing Categories. CoRR abs/2310.03324 (2023) - [i17]Jiang-Xin Shi, Tong Wei, Yuke Xiang, Yufeng Li:
How Re-sampling Helps for Long-Tail Learning? CoRR abs/2310.18236 (2023) - [i16]Weikai Yang, Yukai Guo, Jing Wu, Zheng Wang, Lan-Zhe Guo, Yufeng Li, Shixia Liu:
Interactive Reweighting for Mitigating Label Quality Issues. CoRR abs/2312.05067 (2023) - 2022
- [j13]Tong Wei, Hai Wang, Weiwei Tu, Yufeng Li:
Robust model selection for positive and unlabeled learning with constraints. Sci. China Inf. Sci. 65(11) (2022) - [c53]Lan-Zhe Guo, Yufeng Li:
Class-Imbalanced Semi-Supervised Learning with Adaptive Thresholding. ICML 2022: 8082-8094 - [c52]Jie-Jing Shao, Yunlu Xu, Zhanzhan Cheng, Yufeng Li:
Active Model Adaptation Under Unknown Shift. KDD 2022: 1558-1566 - [c51]Lan-Zhe Guo, Yi-Ge Zhang, Zhi-Fan Wu, Jie-Jing Shao, Yufeng Li:
Robust Semi-Supervised Learning when Not All Classes have Labels. NeurIPS 2022 - [c50]Jie-Jing Shao, Lan-Zhe Guo, Xiaowen Yang, Yufeng Li:
LOG: Active Model Adaptation for Label-Efficient OOD Generalization. NeurIPS 2022 - [c49]Yidong Wang, Hao Chen, Yue Fan, Wang Sun, Ran Tao, Wenxin Hou, Renjie Wang, Linyi Yang, Zhi Zhou, Lan-Zhe Guo, Heli Qi, Zhen Wu, Yufeng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jindong Wang, Xing Xie, Yue Zhang:
USB: A Unified Semi-supervised Learning Benchmark for Classification. NeurIPS 2022 - [c48]Tong Wei, Jiang-Xin Shi, Yufeng Li, Min-Ling Zhang:
Prototypical Classifier for Robust Class-Imbalanced Learning. PAKDD (2) 2022: 44-57 - [i15]Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Yufeng Li:
LAMDA-SSL: Semi-Supervised Learning in Python. CoRR abs/2208.04610 (2022) - [i14]Yidong Wang, Hao Chen, Yue Fan, Wang Sun, Ran Tao, Wenxin Hou, Renjie Wang, Linyi Yang, Zhi Zhou, Lan-Zhe Guo, Heli Qi, Zhen Wu, Yufeng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jindong Wang, Xing Xie, Yue Zhang:
USB: A Unified Semi-supervised Learning Benchmark. CoRR abs/2208.07204 (2022) - [i13]Tong Wei, Zhen Mao, Jiang-Xin Shi, Yufeng Li, Min-Ling Zhang:
A Survey on Extreme Multi-label Learning. CoRR abs/2210.03968 (2022) - 2021
- [j12]Yufeng Li, Lan-Zhe Guo, Zhi-Hua Zhou:
Towards Safe Weakly Supervised Learning. IEEE Trans. Pattern Anal. Mach. Intell. 43(1): 334-346 (2021) - [j11]Yufeng Li, De-Ming Liang:
Lightweight Label Propagation for Large-Scale Network Data. IEEE Trans. Knowl. Data Eng. 33(5): 2071-2082 (2021) - [j10]Changjian Chen, Zhaowei Wang, Jing Wu, Xiting Wang, Lan-Zhe Guo, Yufeng Li, Shixia Liu:
Interactive Graph Construction for Graph-Based Semi-Supervised Learning. IEEE Trans. Vis. Comput. Graph. 27(9): 3701-3716 (2021) - [c47]Tao Han, Wei-Wei Tu, Yufeng Li:
Explanation Consistency Training: Facilitating Consistency-Based Semi-Supervised Learning with Interpretability. AAAI 2021: 7639-7646 - [c46]Zhi-Fan Wu, Tong Wei, Jianwen Jiang, Chaojie Mao, Mingqian Tang, Yufeng Li:
NGC: A Unified Framework for Learning with Open-World Noisy Data. ICCV 2021: 62-71 - [c45]Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yufeng Li, Baigui Sun, Hao Li, Rong Jin:
Dash: Semi-Supervised Learning with Dynamic Thresholding. ICML 2021: 11525-11536 - [c44]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 - [c43]Jie-Jing Shao, Zhanzhan Cheng, Yufeng Li, Shiliang Pu:
Towards Robust Model Reuse in the Presence of Latent Domains. IJCAI 2021: 2957-2963 - [c42]Yufeng Li:
Safe Weakly Supervised Learning. IJCAI 2021: 4951-4955 - [c41]Lan-Zhe Guo, Zhi Zhou, Jie-Jing Shao, Qi Zhang, Feng Kuang, Gao-Le Li, Zhang-Xun Liu, Guobin Wu, Nan Ma, Qun (Tracy) Li, Yufeng Li:
Learning from Imbalanced and Incomplete Supervision with Its Application to Ride-Sharing Liability Judgment. KDD 2021: 487-495 - [c40]Tong Wei, Jiang-Xin Shi, Yufeng Li:
Probabilistic Label Tree for Streaming Multi-Label Learning. KDD 2021: 1801-1811 - [c39]Tong Wei, Wei-Wei Tu, Yufeng Li, Guo-Ping Yang:
Towards Robust Prediction on Tail Labels. KDD 2021: 1812-1820 - [c38]Zhi Zhou, Lan-Zhe Guo, Zhanzhan Cheng, Yufeng Li, Shiliang Pu:
STEP: Out-of-Distribution Detection in the Presence of Limited In-Distribution Labeled Data. NeurIPS 2021: 29168-29180 - [i12]Zhi-Fan Wu, Tong Wei, Jianwen Jiang, Chaojie Mao, Mingqian Tang, Yufeng Li:
NGC: A Unified Framework for Learning with Open-World Noisy Data. CoRR abs/2108.11035 (2021) - [i11]Tong Wei, Jiang-Xin Shi, Wei-Wei Tu, Yufeng Li:
Robust Long-Tailed Learning under Label Noise. CoRR abs/2108.11569 (2021) - [i10]Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yufeng Li, Baigui Sun, Hao Li, Rong Jin:
Dash: Semi-Supervised Learning with Dynamic Thresholding. CoRR abs/2109.00650 (2021) - [i9]Tong Wei, Jiang-Xin Shi, Yufeng Li, Min-Ling Zhang:
Prototypical Classifier for Robust Class-Imbalanced Learning. CoRR abs/2110.11553 (2021) - 2020
- [j9]Miao Xu, Yufeng Li, Zhi-Hua Zhou:
Robust Multi-Label Learning with PRO Loss. IEEE Trans. Knowl. Data Eng. 32(8): 1610-1624 (2020) - [j8]Tong Wei, Yufeng Li:
Does Tail Label Help for Large-Scale Multi-Label Learning? IEEE Trans. Neural Networks Learn. Syst. 31(7): 2315-2324 (2020) - [c37]Lan-Zhe Guo, Feng Kuang, Zhang-Xun Liu, Yufeng Li, Nan Ma, Xiao-Hu Qie:
IWE-Net: Instance Weight Network for Locating Negative Comments and its application to improve Traffic User Experience. AAAI 2020: 4052-4059 - [c36]Qian-Wei Wang, Liang Yang, Yufeng Li:
Learning from Weak-Label Data: A Deep Forest Expedition. AAAI 2020: 6251-6258 - [c35]Yong-Nan Zhu, Yufeng Li:
Semi-Supervised Streaming Learning with Emerging New Labels. AAAI 2020: 7015-7022 - [c34]Zhi-Fan Wu, Yufeng Li:
Semi-Supervised Graph Embedding via Multi-instance Kernel Learning. BigComp 2020: 90-97 - [c33]Yong-Nan Zhu, Xiaotian Luo, Yufeng Li, Bin Bu, Kaibo Zhou, Wenbin Zhang, Mingfan Lu:
Heterogeneous Mini-Graph Neural Network and Its Application to Fraud Invitation Detection. ICDM 2020: 891-899 - [c32]Yu-Xuan Huang, Wang-Zhou Dai, Jian Yang, Le-Wen Cai, Shaofen Cheng, Ruizhang Huang, Yufeng Li, Zhi-Hua Zhou:
Semi-Supervised Abductive Learning and Its Application to Theft Judicial Sentencing. ICDM 2020: 1070-1075 - [c31]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 - [c30]Lan-Zhe Guo, Zhi Zhou, Yufeng Li:
RECORD: Resource Constrained Semi-Supervised Learning under Distribution Shift. KDD 2020: 1636-1644 - [i8]Lan-Zhe Guo, Feng Kuang, Zhang-Xun Liu, Yufeng Li, Nan Ma, Xiao-Hu Qie:
Weakly Supervised Learning Meets Ride-Sharing User Experience Enhancement. CoRR abs/2001.09027 (2020) - [i7]Tong Wei, Feng Shi, Hai Wang, Wei-Wei Tu, Yufeng Li:
MixPUL: Consistency-based Augmentation for Positive and Unlabeled Learning. CoRR abs/2004.09388 (2020)
2010 – 2019
- 2019
- [j7]Yufeng Li, De-Ming Liang:
Safe semi-supervised learning: a brief introduction. Frontiers Comput. Sci. 13(4): 669-676 (2019) - [c29]Yufeng Li, Hai Wang, Tong Wei, Wei-Wei Tu:
Towards Automated Semi-Supervised Learning. AAAI 2019: 4237-4244 - [c28]Tong Wei, Yufeng Li:
Learning Compact Model for Large-Scale Multi-Label Data. AAAI 2019: 5385-5392 - [c27]Feng Shi, Yufeng Li:
Rapid Performance Gain through Active Model Reuse. IJCAI 2019: 3404-3410 - [c26]Qian-Wei Wang, Yufeng Li, Zhi-Hua Zhou:
Partial Label Learning with Unlabeled Data. IJCAI 2019: 3755-3761 - [c25]Tong Wei, Wei-Wei Tu, Yufeng Li:
Learning for Tail Label Data: A Label-Specific Feature Approach. IJCAI 2019: 3842-3848 - [c24]Lan-Zhe Guo, Tao Han, Yufeng Li:
Robust Semi-supervised Representation Learning for Graph-Structured Data. PAKDD (3) 2019: 131-143 - [i6]Lan-Zhe Guo, Yufeng Li, Ming Li, Jinfeng Yi, Bowen Zhou, Zhi-Hua Zhou:
Reliable Weakly Supervised Learning: Maximize Gain and Maintain Safeness. CoRR abs/1904.09743 (2019) - 2018
- [j6]Hai Wang, Shao-Bo Wang, Yufeng Li:
Instance selection method for improving graph-based semi-supervised learning. Frontiers Comput. Sci. 12(4): 725-735 (2018) - [j5]Tong Wei, Lan-Zhe Guo, Yufeng Li, Wei Gao:
Learning safe multi-label prediction for weakly labeled data. Mach. Learn. 107(4): 703-725 (2018) - [c23]Hao-Chen Dong, Yufeng Li, Zhi-Hua Zhou:
Learning From Semi-Supervised Weak-Label Data. AAAI 2018: 2926-2933 - [c22]Lan-Zhe Guo, Yufeng Li:
A General Formulation for Safely Exploiting Weakly Supervised Data. AAAI 2018: 3126-3133 - [c21]Lan-Zhe Guo, Shao-Bo Wang, Yufeng Li:
Large Margin Graph Construction for Semi-Supervised Learning. ICDM Workshops 2018: 1030-1033 - [c20]Tong Wei, Yufeng Li:
Does Tail Label Help for Large-Scale Multi-Label Learning. IJCAI 2018: 2847-2853 - [c19]De-Ming Liang, Yufeng Li:
Lightweight Label Propagation for Large-Scale Network Data. IJCAI 2018: 3421-3427 - [i5]Quanming Yao, Mengshuo Wang, Hugo Jair Escalante, Isabelle Guyon, Yi-Qi Hu, Yufeng Li, Wei-Wei Tu, Qiang Yang, Yang Yu:
Taking Human out of Learning Applications: A Survey on Automated Machine Learning. CoRR abs/1810.13306 (2018) - 2017
- [c18]Yufeng Li, Han-Wen Zha, Zhi-Hua Zhou:
Learning Safe Prediction for Semi-Supervised Regression. AAAI 2017: 2217-2223 - 2016
- [c17]Wei Gao, Lu Wang, Yufeng Li, Zhi-Hua Zhou:
Risk Minimization in the Presence of Label Noise. AAAI 2016: 1575-1581 - [c16]Yufeng Li, James T. Kwok, Zhi-Hua Zhou:
Towards Safe Semi-Supervised Learning for Multivariate Performance Measures. AAAI 2016: 1816-1822 - [c15]Yufeng Li, Shao-Bo Wang, Zhi-Hua Zhou:
Graph Quality Judgement: A Large Margin Expedition. IJCAI 2016: 1725-1731 - [c14]Hai Wang, Shao-Bo Wang, Yufeng Li:
Instance Selection Method for Improving Graph-Based Semi-supervised Learning. PRICAI 2016: 565-573 - [c13]Xinyue Liu, Charu C. Aggarwal, Yufeng Li, Xiangnan Kong, Xinyuan Sun, Saket Sathe:
Kernelized Matrix Factorization for Collaborative Filtering. SDM 2016: 378-386 - 2015
- [j4]Yufeng Li, Zhi-Hua Zhou:
Towards Making Unlabeled Data Never Hurt. IEEE Trans. Pattern Anal. Mach. Intell. 37(1): 175-188 (2015) - 2013
- [j3]Yufeng Li, Ivor W. Tsang, James T. Kwok, Zhi-Hua Zhou:
Convex and scalable weakly labeled SVMs. J. Mach. Learn. Res. 14(1): 2151-2188 (2013) - [j2]Rong Jin, Tianbao Yang, Mehrdad Mahdavi, Yufeng Li, Zhi-Hua Zhou:
Improved Bounds for the Nyström Method With Application to Kernel Classification. IEEE Trans. Inf. Theory 59(10): 6939-6949 (2013) - [c12]Miao Xu, Yufeng Li, Zhi-Hua Zhou:
Multi-Label Learning with PRO Loss. AAAI 2013: 998-1004 - [i4]Yufeng Li, Ivor W. Tsang, James T. Kwok, Zhi-Hua Zhou:
Convex and Scalable Weakly Labeled SVMs. CoRR abs/1303.1271 (2013) - 2012
- [j1]Zhi-Hua Zhou, Min-Ling Zhang, Sheng-Jun Huang, Yufeng Li:
Multi-instance multi-label learning. Artif. Intell. 176(1): 2291-2320 (2012) - [c11]Yufeng Li, Ju-Hua Hu, Yuan Jiang, Zhi-Hua Zhou:
Towards Discovering What Patterns Trigger What Labels. AAAI 2012: 1012-1018 - [c10]Tianbao Yang, Yufeng Li, Mehrdad Mahdavi, Rong Jin, Zhi-Hua Zhou:
Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison. NIPS 2012: 485-493 - 2011
- [c9]Yufeng Li, Zhi-Hua Zhou:
Improving Semi-Supervised Support Vector Machines Through Unlabeled Instances Selection. AAAI 2011: 386-391 - [c8]Yufeng Li, Zhi-Hua Zhou:
Towards Making Unlabeled Data Never Hurt. ICML 2011: 1081-1088 - [c7]Yang Yu, Yufeng Li, Zhi-Hua Zhou:
Diversity Regularized Machine. IJCAI 2011: 1603-1608 - 2010
- [c6]Yufeng Li, James T. Kwok, Zhi-Hua Zhou:
Cost-Sensitive Semi-Supervised Support Vector Machine. AAAI 2010: 500-505 - [i3]Yufeng Li, Zhi-Hua Zhou:
S4VM: Safe Semi-Supervised Support Vector Machine. CoRR abs/1005.1545 (2010)
2000 – 2009
- 2009
- [c5]Yufeng Li, James T. Kwok, Zhi-Hua Zhou:
Semi-supervised learning using label mean. ICML 2009: 633-640 - [c4]De-Chuan Zhan, Ming Li, Yufeng Li, Zhi-Hua Zhou:
Learning instance specific distances using metric propagation. ICML 2009: 1225-1232 - [c3]Zhi-Hua Zhou, Yu-Yin Sun, Yufeng Li:
Multi-instance learning by treating instances as non-I.I.D. samples. ICML 2009: 1249-1256 - [c2]Yufeng Li, James T. Kwok, Ivor W. Tsang, Zhi-Hua Zhou:
A Convex Method for Locating Regions of Interest with Multi-instance Learning. ECML/PKDD (2) 2009: 15-30 - [c1]Yufeng Li, Ivor W. Tsang, James Tin-Yau Kwok, Zhi-Hua Zhou:
Tighter and Convex Maximum Margin Clustering. AISTATS 2009: 344-351 - 2008
- [i2]Zhi-Hua Zhou, Yu-Yin Sun, Yufeng Li:
Multi-Instance Learning by Treating Instances As Non-I.I.D. Samples. CoRR abs/0807.1997 (2008) - [i1]Zhi-Hua Zhou, Min-Ling Zhang, Sheng-Jun Huang, Yufeng Li:
MIML: A Framework for Learning with Ambiguous Objects. CoRR abs/0808.3231 (2008)
Coauthor Index
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