Ming Ji
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Graph regularized transductive classification on heterogeneous information networks
M Ji, Y Sun, M Danilevsky, J Han, J Gao
Machine Learning and Knowledge Discovery in Databases, 570-586, 2010
Ranking-based classification of heterogeneous information networks
M Ji, J Han, M Danilevsky
Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011
MoveMine: Mining moving object data for discovery of animal movement patterns
Z Li, J Han, M Ji, LA Tang, Y Yu, B Ding, JG Lee, R Kays
ACM Transactions on Intelligent Systems and Technology (TIST) 2 (4), 37, 2011
MoveMine: mining moving object databases
Z Li, M Ji, JG Lee, LA Tang, Y Yu, J Han, R Kays
Proceedings of the 2010 international conference on Management of data, 1203 …, 2010
A Variance Minimization Criterion to Feature Selection Using Laplacian Regularization
X He, M Ji, C Zhang, H Bao
Pattern Analysis and Machine Intelligence, IEEE Transactions on, 1-1, 2011
A variance minimization criterion to active learning on graphs
M Ji, J Han
Artificial Intelligence and Statistics, 556-564, 2012
A unified active and semi-supervised learning framework for image compression
X He, M Ji, H Bao
2009 IEEE Conference on Computer Vision and Pattern Recognition, 65-72, 2009
Graph embedding with constraints
X He, M Ji, H Bao
Proceedings of the 21st international jont conference on Artifical …, 2009
A simple algorithm for semi-supervised learning with improved generalization error bound
M Ji, T Yang, B Lin, R Jin, J Han
arXiv preprint arXiv:1206.6412, 2012
Learning search tasks in queries and web pages via graph regularization
M Ji, J Yan, S Gu, J Han, X He, WV Zhang, Z Chen
Proceedings of the 34th international ACM SIGIR conference on Research and …, 2011
Parallel vector field embedding
B Lin, X He, C Zhang, M Ji
The Journal of Machine Learning Research 14 (1), 2945-2977, 2013
Mc-minh: Metagenome clustering using minwise based hashing
Z Rasheed, H Rangwala
Proceedings of the 2013 SIAM International Conference on Data Mining, 677-685, 2013
Mining strong relevance between heterogeneous entities from unstructured biomedical data
M Ji, Q He, J Han, S Spangler
Data Mining and Knowledge Discovery 29 (4), 976-998, 2015
Mining strong relevance between heterogeneous entities from their co-ocurrences
Q He, M Ji, WS Spangler
US Patent App. 14/279,617, 2015
Parallel field ranking
M Ji, B Lin, X He, D Cai, J Han
ACM Transactions on Knowledge Discovery from Data (TKDD) 7 (3), 1-21, 2013
Efficient mining of correlated sequential patterns based on null hypothesis
CX Lin, M Ji, M Danilevsky, J Han
Proceedings of the 2012 international workshop on Web-scale knowledge …, 2012
On the detectability of node grouping in networks
C Wang, H Wang, J Liu, M Ji, L Su, Y Chen, J Han
Proceedings of the 2013 SIAM International Conference on Data Mining, 713-721, 2013
A statistical design approach to unsupervised codeword selection in image retrieval
M Ji, W Zhao, Z Liu
Neurocomputing 157, 323-334, 2015
Graph-based Classification on Heterogeneous Information Networks
M Ji, Y Sun, M Danilevsky, J Han
Semi-supervised learning and relevance search on networked data
M Ji
University of Illinois at Urbana-Champaign, 2014
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