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Cong Li
- Email: congli, at symbol , eecs, dot symbol, ucf, dot symbol, edu
- Office: Room 331, Harris Engineering Complex
- Personal Website: www.eecs.ucf.edu/~congli
- Linkedin: cong-li
- Research Gate: Cong_Li
- Google Scholar: oshcVPUAAAAJ
Bio:
Cong Li is a Ph.D. student in the Machine Learning Lab (ML^2), majored in electrical engineering, at the Department of Electrical Engineering & Computer Science at University of Central Florida in Orlando, Florida. Prior joining ML^2, I received my Bachelor's degrees in both electronic information engineering and mathematics from Tianjin University, China, in 2009. His research interests include machine learning with emphasis on kernel methods, multi-task learning, support vector machines and learning theories.
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2015. Multitask Classification Hypothesis Space With Improved Generalization Bounds. Neural Networks and Learning Systems, IEEE Transactions on. 26(7):1468-1479.
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2015. Pareto-Path Multitask Multiple Kernel Learning. Neural Networks and Learning Systems, IEEE Transactions on. 26(1):51-61.
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2014. Conic Multi-task Classification. Machine Learning and Knowledge Discovery in Databases - ECML/PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings, Part II.
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2013. Kernel-based Distance Metric Learning in the Output Space. Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN).
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2013. Reduced-Rank Local Distance Metric Learning. Machine Learning and Knowledge Discovery in Databases - ECML/PKDD 2013.
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2013. A Unifying Framework for Typical Multitask Multiple Kernel Learning Problems. Neural Networks and Learning Systems, IEEE Transactions on. 25(7):1287-1297.
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2011. Kernel principal subspace Mahalanobis distances for outlier detection. Neural Networks (IJCNN), The 2011 International Joint Conference on.
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2011. Learning in the Feed-forward Random Neural Network: A Critical Review. Perform. Eval.. 68:361–384.