Tri-training: Exploiting unlabeled data using three classifiers ZH Zhou, M Li IEEE Transactions on knowledge and Data Engineering 17 (11), 1529-1541, 2005 | 1607 | 2005 |
Semi-supervised learning by disagreement ZH Zhou, M Li Knowledge and Information Systems 24, 415-439, 2010 | 528 | 2010 |
Improve computer-aided diagnosis with machine learning techniques using undiagnosed samples M Li, ZH Zhou IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and …, 2007 | 504 | 2007 |
Semi-supervised regression with co-training. ZH Zhou, M Li IJCAI 5, 908-913, 2005 | 452 | 2005 |
Supervised deep features for software functional clone detection by exploiting lexical and syntactical information in source code. H Wei, M Li IJCAI, 3034-3040, 2017 | 365 | 2017 |
Semisupervised regression with cotraining-style algorithms ZH Zhou, M Li IEEE Transactions on Knowledge and Data Engineering 19 (11), 1479-1493, 2007 | 295 | 2007 |
Sample-based software defect prediction with active and semi-supervised learning M Li, H Zhang, R Wu, ZH Zhou Automated Software Engineering 19, 201-230, 2012 | 247 | 2012 |
Learning unified features from natural and programming languages for locating buggy source code. X Huo, M Li, ZH Zhou IJCAI 16 (2016), 1606-1612, 2016 | 231 | 2016 |
SETRED: Self-training with editing M Li, ZH Zhou Pacific-Asia Conference on Knowledge Discovery and Data Mining, 611-621, 2005 | 222 | 2005 |
Multi-instance learning based web mining ZH Zhou, K Jiang, M Li Applied intelligence 22, 135-147, 2005 | 173 | 2005 |
Online manifold regularization: A new learning setting and empirical study A Goldberg, M Li, X Zhu Machine Learning and Knowledge Discovery in Databases, 393-407, 2008 | 124 | 2008 |
Enhancing the Unified Features to Locate Buggy Files by Exploiting the Sequential Nature of Source Code. X Huo, M Li IJCAI, 1909-1915, 2017 | 97 | 2017 |
Distributed deep forest and its application to automatic detection of cash-out fraud YL Zhang, J Zhou, W Zheng, J Feng, L Li, Z Liu, M Li, Z Zhang, C Chen, ... ACM Transactions on Intelligent Systems and Technology (TIST) 10 (5), 1-19, 2019 | 95 | 2019 |
Deep transfer bug localization X Huo, F Thung, M Li, D Lo, ST Shi IEEE Transactions on software engineering 47 (7), 1368-1380, 2019 | 92 | 2019 |
Software Defect Detection with Rocus Y Jiang, M Li, ZH Zhou Journal of Computer Science and Technology 26 (2), 328-342, 2011 | 89 | 2011 |
Semi-supervised document retrieval M Li, H Li, ZH Zhou Information Processing & Management 45 (3), 341-355, 2009 | 69 | 2009 |
Learning instance specific distances using metric propagation DC Zhan, M Li, YF Li, ZH Zhou Proceedings of the 26th annual international conference on machine learning …, 2009 | 61 | 2009 |
Machine/deep learning for software engineering: A systematic literature review S Wang, L Huang, A Gao, J Ge, T Zhang, H Feng, I Satyarth, M Li, ... IEEE Transactions on Software Engineering 49 (3), 1188-1231, 2022 | 57 | 2022 |
Control flow graph embedding based on multi-instance decomposition for bug localization X Huo, M Li, ZH Zhou Proceedings of the AAAI conference on artificial intelligence 34 (04), 4223-4230, 2020 | 57 | 2020 |
Cost-effective build outcome prediction using cascaded classifiers A Ni, M Li 2017 IEEE/ACM 14th International Conference on Mining Software Repositories …, 2017 | 57 | 2017 |