Mingmin CHI 池明旻 Associate Professor
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Address:
School of Computer Science,
Fudan University
227 Yuen Cheng-Ying Computer Building
220 Han Dan Road, Shanghai 200433
China
Phone: +86-21-55665495
Email: mmchi AT fudan DOT edu DOT cn
Homepage: in Fudan University
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News
Research interests
- Machine learning
- Graphical models
- Kernel-based methods
- Semi-supervised learning
- Incremental and online learning
- Graphical models
- Its application to
- Image/video copy detection
- Image high-level feature extraction
- Remote sensing image classification
Scientific Reviewer for
- Neurocomputing
- Pattern Recognition Letters
- Pattern Analysis and Applications Journal
- IEEE Transaction on Neural Networks
- IEEE Geoscience and Remote Sensing Letters
- IEEE Transaction on Geoscience and Remote Sensing
- International Journal Artificial Intelligence in Medicine
Courses
- Machine Learning (COMP8003), Fall 2006, Fall 2007, Fall 2008
- Pattern Recognition (372.098.1(INFO130156)), Spring 2007, Spring 2008, Fall 2009
Selected Publications
Book Chapters
- Lorenzo Bruzzone, Mingmin Chi and Mattia Marconcini, "Semisupervised Support Vector Machines for Hyperspectral Image Classification," In Chein-I Chang, editor, Hyperspectral Data Exploitation: Theory and Applications, pp.275-311, John Wiley & Sons, Inc., May 4, 2007.
Journal Articles
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Mingmin Chi, Rui Feng, and Lorenzo Bruzzone, “Classification of hyperspectral remote-sensing data with primal SVM for small-sized training dataset problem, ” Advances in Space Research, vol. 41, no. 11, pp. 1793-1799, 2008.
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Mingmin Chi and Lorenzo Bruzzone, "Semi-Supervised Classification of Hyperspectral Images by SVMs Optimized in the Primal," IEEE Transaction on Geoscience and Remote Sensing, vol. 45, no. 6, pp. 1870-1880, Jun. 2007.
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Lorenzo Bruzzone, Mingmin Chi and Mattia Marconcini, "A novel transductive SVM for semisupervised classification of remote sensing images," IEEE Transaction on Geoscience and Remote Sensing. vol. 44, no. 11, pp. 3363-3373, Nov. 2006.
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Mingmin Chi and Lorenzo Bruzzone, "An ensemble-driven k-NN approach to ill-posed classification problems," Pattern Recognition Letters, vol. 27, no. 4, pp. 301-307, 2005.
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Mingmin Chi and Lorenzo Bruzzone, "A semilabeled-sample-driven bagging technique for ill-posed classification problems," IEEE Geoscience and Remote Sensing Letters, vol. 2, no. 1, pp. 69-73, January 2005.
Conference Papers
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Mingmin Chi, Youdong Miao, Youze Tang, Jon Atli Benediktsson, Xuanjing Huang, "Hierarchical Ensemble Support Cluster Machine," MCS 2009: 252-261.
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Mingmin Chi, Peiwu Zhang, Yingbin Zhao, Rui Feng, Xiangyang Xue, "Web Image Retrieval Reranking with Multi-view Clustering, " WWW 2009: 1189-1190.
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Mingmin Chi, Kun Qian, Jón Atli Benediktsson, “Cluster-based Ensemble Classification for Hyperspectral Remote Sensing Images,” IEEE Int. Geoscience and Remote Sensing Symposium (IGARSS'08), Boston, U.S.A., July, 2008.
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Qing Wang, Liang Zhang, Mingmin Chi, Jiankui Guo, “MTForest: Ensemble Decision Trees based on Multi-Task Learning,” European Conference on Artificial Intelligence (ECAI 2008), Patras, Greece, July, 2008.
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Wei Zhang, Xiangyang Xue, Zichen Sun, Yuefei Guo, Mingmin Chi, and Hong Lu, "Efficient Feature Extraction for Image Classification," 11th IEEE International Conference on Computer Vision (ICCV 2007), Rio de Janeiro, Brazil, Oct. 2007.
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Ilya Zaihrayeu, Lei Sun, Fausto Giunchiglia, Wei Pan, Qi Ju, Mingmin Chi, and Xuanjing Huang, "From Web Directories to Ontologies: Natural Language Processing Challenges," International Semantic Web Conference+Asian Semantic Web Conference (ISWC+ASWC 2007), Busan, Korea, Nov. 2007.
- Mingmin Chi and Lorenzo Bruzzone, "Classification of Hyperspectral Remote Sensing Data with Primal Semi-Supervised SVMs," IEEE Int. Geoscience and Remote Sensing Symposium (IGARSS'07), Barcelona, Spain, July 2007.
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Bin Li, Mingmin Chi, Jianpin Fan and Xiangyang Xue, "Support Cluster Machine," 24th International Conference on Machine Learning (ICML'07), Corvallis, USA, June 2007.
- Olivier Chapelle, Mingmin Chi and Alexander Zien, "A Continuation Method for Semi-Supervised SVMs," 23rd International Conference on Machine Learning (ICML'06), Pittsburgh, USA, June 2006.