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ORCIDMing Li 0005
Person information
- affiliation: Nanjing University, National Key Laboratory for Novel Software Technology, China
Other persons with the same name
- Ming Li — disambiguation page
- Ming Li 0001
![[0000-0002-2157-2775]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-2157-2775")
— University of Waterloo, ON, Canada (and 3 more) - Ming Li 0002 — East China Normal University, Shanghai, China (and 1 more)
- Ming Li 0003 (aka: Ming (Fred) Li) — University of Arizona, Tucson, AZ, USA (and 2 more)
- Ming Li 0004 — Xidian University, National Key Lab of Radar Signal Processing, Xi'an, China
- Ming Li 0006 — University of Texas at Arlington, TX, USA (and 2 more)
- Ming Li 0007 — California State University, Fresno, CA, USA (and 1 more)
- Ming Li 0008 — Worcester Polytechnic Institute, MA, USA
- Ming Li 0009 — IBM T. J. Watson Research Center, Yorktown Heights, NY, USA (and 1 more)
- Ming Li 0010 — Deakin University, VIC, Australia
- Ming Li 0011 — Dalian University of Technology, School of Information and Communication Engineering, China (and 2 more)
- Ming Li 0012 — Taiyuan University of Technology, College of Mathematics, China (and 1 more)
- Ming Li 0013 — China University of Mining & Technology, Xuzhou, China
- Ming Li 0014 — Unilever Corporate Research, Sharnbrook, Bedford, UK
- Ming Li 0015 — Lanzhou University of Technology, China
- Ming Li 0016 — RWTH Aachen University, Germany
- Ming Li 0017 — Zhejiang University, State Key Laboratory of CAD&CG, China
- Ming Li 0018 — Max-Planck-Institut für Informatik, Saarbrücken, Germany
- Ming Li 0019 — Carleton University, Ottawa, ON, Canada
- Ming Li 0020 — Google (and 1 more)
- Ming Li 0021 — Oracle (and 1 more)
- Ming Li 0022 — Vanderbilt University, Department of Biostatistics, Nashville, TN, USA
- Ming Li 0023 — Simon Fraser University, Burnaby, BC, Canada
- Ming Li 0024 — Concordia University, Department of Economics, Montreal, QC, Canada
- Ming Li 0025 — Chinese Academy of Sciences, Institute of Semiconductors, China (and 1 more)
- Ming Li 0026 — Duke Kunshan University, Data Science Research Center, China (and 3 more)
- Ming Li 0028 — National University of Defense Technology, College of Mechatronic Engineering and Automation, Changsha, China
- Ming Li 0029 — Beihang University, School of Automation Science and Electrical Engineering, Beijing, China (and 2 more)
- Ming Li 0030 — Auburn University MRI Research Center, Auburn, USA
- Ming Li 0031 — China University of Mining and Technology, School of Computer Science and Technology, Xuzhou, China
- Ming Li 0032 — Heidelberg University, Institute of Geography, Germany
- Ming Li 0033 — Chinese Academy of Sciences, Institute of Information Engineering, State Key Laboratory of Information Security, Beijing, China
- Ming Li 0034 — Beihang University, Institute of Solid Mechanics, Beijing, China
- Ming Li 0035 — Aalto University, Department of Computer Science, Espoo, Finland
- Ming Li 0036 — Honghe University, Department of Mathematics, Mengzi, Yunnan, China
- Ming Li 0037 — Wuhan University, State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, China
- Ming Li 0038 — Second Military Medical University, Changhai Hospital, Department of Orthopaedics, Shanghai, China
- Ming Li 0039 — China Jiliang University, Department of Mathematics, Hangzhou, China
- Ming Li 0040 — Nanchang University, ISST, China (and 1 more)
- Ming Li 0041 — Tianjin Normal University, Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, China (and 1 more)
- Ming Li 0042 — Hamburg University of Technology, Germany
- Ming Li 0043 — Unilever China (and 1 more)
- Ming Li 0044 — Colorado School of Mines, Department of Electrical Engineering and Computer Science, Golden, CO, USA
- Ming Li 0045 — Shanghai Jiao Tong University, Institute of Image Processing and Pattern Recognition, China
- Ming Li 0046 — Yanshan University, College of Electrical Engineering, Qinhuangdao, China
- Ming Li 0047 — Beijing Jiaotong University, School of Electronic and Information Engineering, China
- Ming Li 0048 — Sun Yat-sen University, School of Geography and Planning, Guangzhou, China
- Ming Li 0049 — Jinan University, College of Information Science and Technology, China
- Ming Li 0051 — China University of Petroleum, School of Economics and Management, Beijing, China
- Ming Li 0052 — National Institutes of Health, Center for Interventional Oncology / National Heart, Lung, and Blood Institute, Bethesda, MD, USA (and 1 more)
- Ming Li 0053 — Macquarie University, Sydney, NSW, Australia (and 3 more)
- Ming Li 0054 — Beihang University, School of Transportation Science and Engineering / Beijing Advanced Innovation Center for Big Data and Brain Computing, Beijing, China
- Ming Li 0055 — Hong Kong Polytechnic University, Department of Industrial and Systems Engineering, Hong Kong (and 2 more)
- Ming Li 0056 — Nanchang Hangkong University, MOE Key Laboratory of Nondestructive Testing, China (and 1 more)
- Ming Li 0057 — Ocean University of China, College of Engineering, Department of Automation, Qingdao, China (and 1 more)
- Ming Li 0058 — Shenyang University of Technology, School of Electrical Engineering, China
- Ming Li 0059 — National University of Defense Technology, College of Meteorology and Oceanography, Nanjing, China
- Ming Li 0060 — Harbin Engineering University, College of Computer Science and Technology, China
- Ming Li 0061 — Rizhao People's Hospital, Department of Nuclear Medicine, China
- Ming Li 0062 — CRRC Tangshan Company, Ltd., Tangshan, China
- Ming Li 0063 — Harbin Institute of Technology, Communication Research Center, China
- Ming Li 0064 — Beijing Institute of Technology, State Key Laboratory of Explosion Science and Technology, China
- Ming Li 0065 — Zhejiang Normal University, Department of Computer Science, Jinhua, China (and 2 more)
- Ming Li 0066 — National University of Defense Technology, College of Electronic Science and Technology, State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, Changsha, China
- Ming Li 0067 — Lappeenranta University of Technology, LUT, Laboratory of Intelligent Machines, Department of Mechanical Engineering, Finland
- Ming Li 0068 — University of Amsterdam, IRLab, Netherlands (and 1 more)
- Ming Li 0069 — Nanjing University, School of Electronic Science and Engineering, China
- Ming Li 0070 — China University of Petroleum, School of Science, Qingdao, China (and 1 more)
- Ming Li 0071 — Jiangsu Ocean University, Department of Computer Science and Technology, China (and 1 more)
- Ming Li 0072 — Wuhan University of Technology, China (and 1 more)
- Ming Li 0073 — National University of Singapore, Institute of Data Science, Singapore (and 2 more)
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2020 – today
- 2024
[j28]Hao-Yuan He, Wang-Zhou Dai, Ming Li:
Reduced implication-bias logic loss for neuro-symbolic learning. Mach. Learn. 113(6): 3357-3377 (2024)- [j27]Zheng Xie, Yu Liu, Hao-Yuan He, Ming Li, Zhi-Hua Zhou:
Weakly Supervised AUC Optimization: A Unified Partial AUC Approach. IEEE Trans. Pattern Anal. Mach. Intell. 46(7): 4780-4795 (2024) - [j26]Liang Jin, Shixuan Gu, Donglai Wei, Jason Ken Adhinarta, Kaiming Kuang, Yongjie Jessica Zhang, Hanspeter Pfister, Bingbing Ni, Jiancheng Yang, Ming Li:
: A Large-Scale Benchmark for Rib Labeling and Anatomical Centerline Extraction. IEEE Trans. Medical Imaging 43(1): 570-581 (2024) - [j25]Wei Zhao, Weidao Chen, Ge Li, Du Lei, Jiancheng Yang, Yanjing Chen, Yingjia Jiang, Jiangfen Wu, Bingbing Ni, Yeqi Sun, Shaokang Wang, Yingli Sun, Ming Li, Jun Liu:
GMILT: A Novel Transformer Network That Can Noninvasively Predict EGFR Mutation Status. IEEE Trans. Neural Networks Learn. Syst. 35(6): 7324-7338 (2024) - [c42]Zheng Xie, Yu Liu, Ming Li:
AUC Optimization from Multiple Unlabeled Datasets. AAAI 2024: 16058-16066 - [c41]Hao-Yuan He, Hui Sun, Zheng Xie, Ming Li:
Ambiguity-Aware Abductive Learning. ICML 2024 - [c40]Rui Kong, Chenyang Wu, Chen-Xiao Gao, Zongzhang Zhang, Ming Li:
Efficient and Stable Offline-to-online Reinforcement Learning via Continual Policy Revitalization. IJCAI 2024: 4317-4325 - [c39]Yali Du, Hui Sun, Ming Li:
A Joint Learning Model with Variational Interaction for Multilingual Program Translation. ASE 2024: 1907-1918 - [c38]Yu Liu, Qinglin Jia, Shuting Shi, Chuhan Wu, Zhaocheng Du, Zheng Xie, Ruiming Tang, Muyu Zhang, Ming Li:
Ranking-Aware Unbiased Post-Click Conversion Rate Estimation via AUC Optimization on Entire Exposure Space. RecSys 2024: 360-369 - [i15]Jiancheng Yang, Rui Shi, Liang Jin, Xiaoyang Huang, Kaiming Kuang, Donglai Wei, Shixuan Gu, Jianying Liu, Pengfei Liu, Zhizhong Chai, Yongjie Xiao, Hao Chen, Liming Xu, Bang Du, Xiangyi Yan, Hao Tang, Adam M. Alessio, Gregory Holste, Jiapeng Zhang, Xiaoming Wang, Jianye He, Lixuan Che, Hanspeter Pfister, Ming Li, Bingbing Ni:
Deep Rib Fracture Instance Segmentation and Classification from CT on the RibFrac Challenge. CoRR abs/2402.09372 (2024) - [i14]Yali Du, Hui Sun, Ming Li:
A Joint Learning Model with Variational Interaction for Multilingual Program Translation. CoRR abs/2408.14515 (2024) - 2023
- [j24]Hui Sun, Ming Li:
Enhancing unsupervised domain adaptation by exploiting the conceptual consistency of multiple self-supervised tasks. Sci. China Inf. Sci. 66(4) (2023) - [j23]Simin Wang, Liguo Huang, Amiao Gao, Jidong Ge, Tengfei Zhang, Haitao Feng, Ishna Satyarth, Ming Li, He Zhang, Vincent Ng:
Machine/Deep Learning for Software Engineering: A Systematic Literature Review. IEEE Trans. Software Eng. 49(3): 1188-1231 (2023) - [c37]Hui Sun, Zheng Xie, Xin-Ye Li, Ming Li:
Cooperative and Adversarial Learning: Co-enhancing Discriminability and Transferability in Domain Adaptation. AAAI 2023: 9909-9917 - [c36]Zheng Xie, Hui Sun, Ming Li:
Semi-supervised Learning with Support Isolation by Small-Paced Self-Training. AAAI 2023: 10510-10518 - [c35]Yali Du, Yi-Fan Ma, Zheng Xie, Ming Li:
Beyond Lexical Consistency: Preserving Semantic Consistency for Program Translation. ICDM 2023: 91-100 - [c34]Yunbo Lyu, Thanh Le-Cong, Hong Jin Kang, Ratnadira Widyasari, Zhipeng Zhao, Xuan-Bach Dinh Le, Ming Li, David Lo:
CHRONOS: Time-Aware Zero-Shot Identification of Libraries from Vulnerability Reports. ICSE 2023: 1033-1045 - [c33]Yi-Fan Ma, Yali Du, Ming Li:
Capturing the Long-Distance Dependency in the Control Flow Graph via Structural-Guided Attention for Bug Localization. IJCAI 2023: 2242-2250 - [i13]Yunbo Lyu, Thanh Le-Cong, Hong Jin Kang, Ratnadira Widyasari, Zhipeng Zhao, Xuan-Bach Dinh Le, Ming Li, David Lo:
CHRONOS: Time-Aware Zero-Shot Identification of Libraries from Vulnerability Reports. CoRR abs/2301.03944 (2023) - [i12]Xin-Ye Li, Jiang-Tian Xue, Zheng Xie, Ming Li:
Think Outside the Code: Brainstorming Boosts Large Language Models in Code Generation. CoRR abs/2305.10679 (2023) - [i11]Zheng Xie, Yu Liu, Hao-Yuan He, Ming Li, Zhi-Hua Zhou:
Weakly Supervised AUC Optimization: A Unified Partial AUC Approach. CoRR abs/2305.14258 (2023) - [i10]Zheng Xie, Yu Liu, Ming Li:
AUC Optimization from Multiple Unlabeled Datasets. CoRR abs/2305.15776 (2023) - [i9]Tianyang Zhong, Wei Zhao, Yutong Zhang, Yi Pan, Peixin Dong, Zuowei Jiang, Xiaoyan Kui, Youlan Shang, Li Yang, Yaonai Wei, Longtao Yang, Hao Chen, Huan Zhao, Yuxiao Liu, Ning Zhu, Yiwei Li, Yisong Wang, Jiaqi Yao, Jiaqi Wang, Ying Zeng, Lei He, Chao Zheng, Zhixue Zhang, Ming Li, Zhengliang Liu, Haixing Dai, Zihao Wu, Lu Zhang, Shu Zhang, Xiaoyan Cai, Xintao Hu, Shijie Zhao, Xi Jiang, Xin Zhang, Xiang Li, Dajiang Zhu, Lei Guo, Dinggang Shen, Junwei Han, Tianming Liu, Jun Liu, Tuo Zhang:
ChatRadio-Valuer: A Chat Large Language Model for Generalizable Radiology Report Generation Based on Multi-institution and Multi-system Data. CoRR abs/2310.05242 (2023) - [i8]Chengran Yang, Jiakun Liu, Bowen Xu, Christoph Treude, Yunbo Lyu, Junda He, Ming Li, David Lo:
APIDocBooster: An Extract-Then-Abstract Framework Leveraging Large Language Models for Augmenting API Documentation. CoRR abs/2312.10934 (2023) - 2022
- [j22]Yi-Fan Ma, Ming Li:
The flowing nature matters: feature learning from the control flow graph of source code for bug localization. Mach. Learn. 111(3): 853-870 (2022) - [c32]Yi-Fan Ma, Ming Li:
Learning from the Multi-Level Abstraction of the Control Flow Graph via Alternating Propagation for Bug Localization. ICDM 2022: 299-308 - [i7]Haoyuan He, Wang-Zhou Dai, Ming Li, Yu Liu, Yongchang Ma:
Reduced Implication-bias Logic Loss for Neuro-Symbolic Learning. CoRR abs/2208.06838 (2022) - [i6]Liang Jin, Shixuan Gu, Donglai Wei, Kaiming Kuang, Hanspeter Pfister, Bingbing Ni, Jiancheng Yang, Ming Li:
RibSeg v2: A Large-scale Benchmark for Rib Labeling and Anatomical Centerline Extraction. CoRR abs/2210.09309 (2022) - 2021
- [j21]Xuan Huo, Ferdian Thung, Ming Li, David Lo, Shu-Ting Shi:
Deep Transfer Bug Localization. IEEE Trans. Software Eng. 47(7): 1368-1380 (2021) - [c31]Feng Xu, Shengyi Jiang, Hao Yin, Zongzhang Zhang, Yang Yu, Ming Li, Dong Li, Wulong Liu:
Enhancing Context-Based Meta-Reinforcement Learning Algorithms via An Efficient Task Encoder (Student Abstract). AAAI 2021: 15937-15938 - [c30]Fan Yan, Ming Li:
Towards Generating Summaries for Lexically Confusing Code through Code Erosion. IJCAI 2021: 3721-3727 - 2020
- [j20]Jinpeng Li, Yishan Luo, Lin Shi, Xin Zhang, Ming Li, Bing Zhang, Defeng Wang:
Automatic fetal brain extraction from 2D in utero fetal MRI slices using deep neural network. Neurocomputing 378: 335-349 (2020) - [j19]Yaojing Wang, Yuan Yao, Hanghang Tong, Xuan Huo, Ming Li, Feng Xu, Jian Lu:
Enhancing supervised bug localization with metadata and stack-trace. Knowl. Inf. Syst. 62(6): 2461-2484 (2020) - [j18]Fei Wu, Cewu Lu, Mingjie Zhu, Hao Chen, Jun Zhu, Kai Yu, Lei Li, Ming Li, Qianfeng Chen, Xi Li, Xudong Cao, Zhongyuan Wang, Zhengjun Zha, Yueting Zhuang, Yunhe Pan:
Towards a new generation of artificial intelligence in China. Nat. Mach. Intell. 2(6): 312-316 (2020) - [c29]Xuan Huo, Ming Li, Zhi-Hua Zhou:
Control Flow Graph Embedding Based on Multi-Instance Decomposition for Bug Localization. AAAI 2020: 4223-4230 - [c28]Shu-Ting Shi, Wenhao Zheng, Jun Tang, Qing-Guo Chen, Yao Hu, Jianke Zhu, Ming Li:
Deep Time-Stream Framework for Click-through Rate Prediction by Tracking Interest Evolution. AAAI 2020: 5726-5733 - [c27]Jia-Wei Mi, Shu-Ting Shi, Ming Li:
Learning Code Changes by Exploiting Bidirectional Converting Deviation. ACML 2020: 481-496 - [i5]Shu-Ting Shi, Wenhao Zheng, Jun Tang, Qing-Guo Chen, Yao Hu, Jianke Zhu, Ming Li:
Deep Time-Stream Framework for Click-Through Rate Prediction by Tracking Interest Evolution. CoRR abs/2001.03025 (2020) - [i4]Simin Wang, Liguo Huang, Jidong Ge, Tengfei Zhang, Haitao Feng, Ming Li, He Zhang, Vincent Ng:
Synergy between Machine/Deep Learning and Software Engineering: How Far Are We? CoRR abs/2008.05515 (2020)
2010 – 2019
- 2019
- [j17]Wenhao Zheng, Hong-Yu Zhou, Ming Li, Jianxin Wu:
CodeAttention: translating source code to comments by exploiting the code constructs. Frontiers Comput. Sci. 13(3): 565-578 (2019) - [j16]Xuan Huo, Ming Li:
On cost-effective software defect prediction: Classification or ranking? Neurocomputing 363: 339-350 (2019) - [j15]Ya-Lin Zhang, Jun Zhou, Wenhao Zheng, Ji Feng, Longfei Li, Ziqi Liu, Ming Li, Zhiqiang Zhang, Chaochao Chen, Xiaolong Li, Yuan (Alan) Qi, Zhi-Hua Zhou:
Distributed Deep Forest and its Application to Automatic Detection of Cash-Out Fraud. ACM Trans. Intell. Syst. Technol. 10(5): 55:1-55:19 (2019) - [c26]Shu-Ting Shi, Ming Li, David Lo, Ferdian Thung, Xuan Huo:
Automatic Code Review by Learning the Revision of Source Code. AAAI 2019: 4910-4917 - [c25]Yan-Ya Zhang, Ming Li:
Find Me if You Can: Deep Software Clone Detection by Exploiting the Contest between the Plagiarist and the Detector. AAAI 2019: 5813-5820 - [c24]Yudong Zhang, Wenhao Zheng, Ming Li:
Learning Uniform Semantic Features for Natural Language and Programming Language Globally, Locally and Sequentially. AAAI 2019: 5845-5852 - [c23]Bin-Bin Yang, Wei Gao, Ming Li:
On the Robust Splitting Criterion of Random Forest. ICDM 2019: 1420-1425 - [c22]Heng-Yi Li, Ming Li, Zhi-Hua Zhou:
Towards One Reusable Model for Various Software Defect Mining Tasks. PAKDD (3) 2019: 212-224 - [c21]Heng-Yi Li, Shu-Ting Shi, Ferdian Thung, Xuan Huo, Bowen Xu, Ming Li, David Lo:
DeepReview: Automatic Code Review Using Deep Multi-instance Learning. PAKDD (2) 2019: 318-330 - [i3]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
- [j14]Jiaming Lu, Xin Wang, Zhao Qing, Zhu Li, Wen Zhang, Ying Liu, Lihua Yuan, Le Cheng, Ming Li, Bin Zhu, Xin Zhang, Qing X. Yang, Bing Zhang:
Detectability and reproducibility of the olfactory fMRI signal under the influence of magnetic susceptibility artifacts in the primary olfactory cortex. NeuroImage 178: 613-621 (2018) - [c20]Zheng Xie, Ming Li:
Semi-Supervised AUC Optimization Without Guessing Labels of Unlabeled Data. AAAI 2018: 4310-4317 - [c19]Xuan Huo, Yang Yang, Ming Li, De-Chuan Zhan:
Learning Semantic Features for Software Defect Prediction by Code Comments Embedding. ICDM 2018: 1049-1054 - [c18]Zhi-Yu Shen, Ming Li:
T2S: Domain Adaptation Via Model-Independent Inverse Mapping and Model Reuse. ICDM 2018: 1224-1229 - [c17]Ansong Ni, Ming Li:
ACONA: active online model adaptation for predicting continuous integration build failures. ICSE (Companion Volume) 2018: 366-367 - [c16]Huihui Wei, Ming Li:
Positive and Unlabeled Learning for Detecting Software Functional Clones with Adversarial Training. IJCAI 2018: 2840-2846 - [c15]Zheng Xie, Ming Li:
Cutting the Software Building Efforts in Continuous Integration by Semi-Supervised Online AUC Optimization. IJCAI 2018: 2875-2881 - [e2]Ming Li, Xiaoyin Wang, David Lo:
Proceedings of the 7th International Workshop on Software Mining, ASE 2018, Montpellier, France, September 3, 2018. ACM 2018 [contents] - [i2]Ya-Lin Zhang, Jun Zhou, Wenhao Zheng, Ji Feng, Longfei Li, Ziqi Liu, Ming Li, Zhiqiang Zhang, Chaochao Chen, Xiaolong Li, Zhi-Hua Zhou:
Distributed Deep Forest and its Application to Automatic Detection of Cash-out Fraud. CoRR abs/1805.04234 (2018) - 2017
- [j13]Wenhao Zheng, Ming Li:
The best answer prediction by exploiting heterogeneous data on software development Q&A forum. Neurocomputing 269: 212-219 (2017) - [c14]Xuan Huo, Ming Li:
Enhancing the Unified Features to Locate Buggy Files by Exploiting the Sequential Nature of Source Code. IJCAI 2017: 1909-1915 - [c13]Huihui Wei, Ming Li:
Supervised Deep Features for Software Functional Clone Detection by Exploiting Lexical and Syntactical Information in Source Code. IJCAI 2017: 3034-3040 - [c12]Ansong Ni, Ming Li:
Cost-effective build outcome prediction using cascaded classifiers. MSR 2017: 455-458 - [i1]Wenhao Zheng, Hong-Yu Zhou, Ming Li, Jianxin Wu:
Code Attention: Translating Code to Comments by Exploiting Domain Features. CoRR abs/1709.07642 (2017) - 2016
- [c11]Xuan Huo, Ming Li, Zhi-Hua Zhou:
Learning Unified Features from Natural and Programming Languages for Locating Buggy Source Code. IJCAI 2016: 1606-1612 - [e1]Ming Li, Xiaoyin Wang, Lucia:
Proceedings of the 5th International Workshop on Software Mining, SoftwareMining@ASE 2016, Singapore, Singapore, September 3, 2016. ACM 2016, ISBN 978-1-4503-4511-8 [contents] - 2015
- [j12]Ming Li, Hongyu Zhang, David Lo, Lucia:
Improving Software Quality and Productivity Leveraging Mining Techniques: [Summary of the Second Workshop on Software Mining, at ASE 2013]. ACM SIGSOFT Softw. Eng. Notes 40(1): 1-2 (2015) - [c10]Tien-Duy B. Le, David Lo, Ming Li:
Constrained feature selection for localizing faults. ICSME 2015: 501-505 - 2013
- [c9]Tao Li, Ming Li:
PerGrab: Adapting Grabbing Gesture Recognition for Personalized Non-contact HCI. IScIDE 2013: 740-747 - 2012
- [j11]Ming Li, Hongyu Zhang, Rongxin Wu, Zhi-Hua Zhou:
Sample-based software defect prediction with active and semi-supervised learning. Autom. Softw. Eng. 19(2): 201-230 (2012) - 2011
- [j10]Yuan Jiang, Ming Li, Zhi-Hua Zhou:
Software Defect Detection with Rocus. J. Comput. Sci. Technol. 26(2): 328-342 (2011) - 2010
- [j9]Ming Li, Wei Wang, Zhi-Hua Zhou:
Exploiting remote learners in Internet environment with agents. Sci. China Inf. Sci. 53(1): 64-76 (2010) - [j8]Zhi-Hua Zhou, Ming Li:
Semi-supervised learning by disagreement. Knowl. Inf. Syst. 24(3): 415-439 (2010)
2000 – 2009
- 2009
- [j7]Ming Li, Hang Li, Zhi-Hua Zhou:
Semi-supervised document retrieval. Inf. Process. Manag. 45(3): 341-355 (2009) - [j6]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) - [c8]De-Chuan Zhan, Ming Li, Yufeng Li, Zhi-Hua Zhou:
Learning instance specific distances using metric propagation. ICML 2009: 1225-1232 - [c7]Ming Li, Xiao-Bing Xue, Zhi-Hua Zhou:
Exploiting Multi-Modal Interactions: A Unified Framework. IJCAI 2009: 1120-1125 - 2008
- [c6]Ming Li, Zhongfei (Mark) Zhang, Zhi-Hua Zhou:
Mining Bulletin Board Systems Using Community Generation. PAKDD 2008: 209-221 - [c5]Andrew B. Goldberg, Ming Li, Xiaojin Zhu:
Online Manifold Regularization: A New Learning Setting and Empirical Study. ECML/PKDD (1) 2008: 393-407 - 2007
- [j5]Yang Yu, De-Chuan Zhan, Xu-Ying Liu, Ming Li, Zhi-Hua Zhou:
Predicting Future Customers via Ensembling Gradually Expanded Trees. Int. J. Data Warehous. Min. 3(2): 12-21 (2007) - [j4]Zhi-Hua Zhou, Ming Li:
Semisupervised Regression with Cotraining-Style Algorithms. IEEE Trans. Knowl. Data Eng. 19(11): 1479-1493 (2007) - [j3]Ming Li, Zhi-Hua Zhou:
Improve Computer-Aided Diagnosis With Machine Learning Techniques Using Undiagnosed Samples. IEEE Trans. Syst. Man Cybern. Part A 37(6): 1088-1098 (2007) - 2006
- [c4]Fei Chen, Lin Shang, Ming Li, Zhaoqian Chen, Shifu Chen:
Mining Frequent Patterns based on Compressed FP-tree without Conditional FP-tree Generation. GrC 2006: 478-481 - [c3]Yuan Jiang, Ming Li, Zhi-Hua Zhou:
Generation of Comprehensible Hypotheses from Gene Expression Data. BioDM 2006: 116-123 - 2005
- [j2]Zhi-Hua Zhou, Kai Jiang, Ming Li:
Multi-Instance Learning Based Web Mining. Appl. Intell. 22(2): 135-147 (2005) - [j1]Zhi-Hua Zhou, Ming Li:
Tri-Training: Exploiting Unlabeled Data Using Three Classifiers. IEEE Trans. Knowl. Data Eng. 17(11): 1529-1541 (2005) - [c2]Zhi-Hua Zhou, Ming Li:
Semi-Supervised Regression with Co-Training. IJCAI 2005: 908-916 - [c1]Ming Li, Zhi-Hua Zhou:
SETRED: Self-training with Editing. PAKDD 2005: 611-621
Coauthor Index
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