Ming Li

According to our database1, Ming Li authored at least 46 papers between 2005 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2020
Enhancing supervised bug localization with metadata and stack-trace.
Knowl. Inf. Syst., 2020

Deep Time-Stream Framework for Click-through Rate Prediction by Tracking Interest Evolution.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Control Flow Graph Embedding Based on Multi-Instance Decomposition for Bug Localization.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Distributed Deep Forest and its Application to Automatic Detection of Cash-Out Fraud.
ACM Trans. Intell. Syst. Technol., 2019

CodeAttention: translating source code to comments by exploiting the code constructs.
Frontiers Comput. Sci., 2019

Reliable Weakly Supervised Learning: Maximize Gain and Maintain Safeness.
CoRR, 2019

DeepReview: Automatic Code Review Using Deep Multi-instance Learning.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

Towards One Reusable Model for Various Software Defect Mining Tasks.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

On the Robust Splitting Criterion of Random Forest.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Learning Uniform Semantic Features for Natural Language and Programming Language Globally, Locally and Sequentially.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Find Me if You Can: Deep Software Clone Detection by Exploiting the Contest between the Plagiarist and the Detector.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Automatic Code Review by Learning the Revision of Source Code.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Distributed Deep Forest and its Application to Automatic Detection of Cash-out Fraud.
CoRR, 2018

Cutting the Software Building Efforts in Continuous Integration by Semi-Supervised Online AUC Optimization.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Positive and Unlabeled Learning for Detecting Software Functional Clones with Adversarial Training.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

ACONA: active online model adaptation for predicting continuous integration build failures.
Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings, 2018

T2S: Domain Adaptation Via Model-Independent Inverse Mapping and Model Reuse.
Proceedings of the IEEE International Conference on Data Mining, 2018

Learning Semantic Features for Software Defect Prediction by Code Comments Embedding.
Proceedings of the IEEE International Conference on Data Mining, 2018

Semi-Supervised AUC Optimization Without Guessing Labels of Unlabeled Data.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
The best answer prediction by exploiting heterogeneous data on software development Q&A forum.
Neurocomputing, 2017

Code Attention: Translating Code to Comments by Exploiting Domain Features.
CoRR, 2017

Cost-effective build outcome prediction using cascaded classifiers.
Proceedings of the 14th International Conference on Mining Software Repositories, 2017

Supervised Deep Features for Software Functional Clone Detection by Exploiting Lexical and Syntactical Information in Source Code.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Enhancing the Unified Features to Locate Buggy Files by Exploiting the Sequential Nature of Source Code.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016
Learning Unified Features from Natural and Programming Languages for Locating Buggy Source Code.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015
Improving Software Quality and Productivity Leveraging Mining Techniques: [Summary of the Second Workshop on Software Mining, at ASE 2013].
ACM SIGSOFT Softw. Eng. Notes, 2015

Constrained feature selection for localizing faults.
Proceedings of the 2015 IEEE International Conference on Software Maintenance and Evolution, 2015

2013
PerGrab: Adapting Grabbing Gesture Recognition for Personalized Non-contact HCI.
Proceedings of the Intelligence Science and Big Data Engineering, 2013

2012
Sample-based software defect prediction with active and semi-supervised learning.
Autom. Softw. Eng., 2012

2011
Software Defect Detection with Rocus.
J. Comput. Sci. Technol., 2011

2010
Semi-supervised learning by disagreement.
Knowl. Inf. Syst., 2010

Exploiting remote learners in Internet environment with agents.
Sci. China Inf. Sci., 2010

2009
Mining extremely small data sets with application to software reuse.
Softw. Pract. Exp., 2009

Semi-supervised document retrieval.
Inf. Process. Manag., 2009

Exploiting Multi-Modal Interactions: A Unified Framework.
Proceedings of the IJCAI 2009, 2009

Learning instance specific distances using metric propagation.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Online Manifold Regularization: A New Learning Setting and Empirical Study.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

Mining Bulletin Board Systems Using Community Generation.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2008

2007
Improve Computer-Aided Diagnosis With Machine Learning Techniques Using Undiagnosed Samples.
IEEE Trans. Syst. Man Cybern. Part A, 2007

Semisupervised Regression with Cotraining-Style Algorithms.
IEEE Trans. Knowl. Data Eng., 2007

Predicting Future Customers via Ensembling Gradually Expanded Trees.
Int. J. Data Warehous. Min., 2007

2006
Generation of Comprehensible Hypotheses from Gene Expression Data.
Proceedings of the Data Mining for Biomedical Applications, PAKDD 2006 Workshop, 2006

2005
Tri-Training: Exploiting Unlabeled Data Using Three Classifiers.
IEEE Trans. Knowl. Data Eng., 2005

Multi-Instance Learning Based Web Mining.
Appl. Intell., 2005

SETRED: Self-training with Editing.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2005

Semi-Supervised Regression with Co-Training.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005


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