| Address: | Institut für Numerische Simulation Wegelerstr. 4 (Flachbau) 53115 Bonn Germany |
| Office: | We4 0.024 |
| Phone: | +49 228 73 4091 |
| E-Mail: | fuxin.li ins.uni-bonn.de |
I am a post-doctoral researcher in the Sminchisescu group, INS, University of Bonn. Previously, I got my bachelor degree on 2001 in Zhejiang University, and my Ph.D. degree on 2008 in the Institute of Automation, Chinese Academy of Sciences, with a dissertation on
I am broadly interested in many machine learning algorithms and applications, but mainly the frequentist type, such as kernel methods, boosting, matrix learning methods such as metric learning, and applications in all sorts of areas. I have application experiences in proteomics, natural language processing and most recently, computer vision. Collaborating with João Carreira and Cristian Sminchisescu, our object segmentation/recognition system won the PASCAL VOC 2009 Segmentation Challenge. I mainly work in the recognition part of the system, on how to correctly classify and generate the final segmentation from a pool of initial figure-ground segmentations.
Theoretically, I am more interested in the optimization part of machine learning, looking for new optimization paradigms, algorithms and theoretical justifications. Some of my recent works focused on learning kernels and metrics, either from a kernel-matrix learning perspective or from the perspective of nonlinear feature selection inside a kernel. They are published in AISTATS 2009 and 2010. In particular, the trust-region inexact Newton method from our 2009 AISTATS paper is the fastest algorithm to-date to learn a full-rank positive-definite kernel matrix.
On a larger scale, I have the drive to create the real learning machine that has more and more capabilities, that will in the end surpass human intelligence and engage in the battle with genetically heavily modified human-being in the future. But I also believe that Rome is not built in one day. Therefore, I'm also interested in alternative but practical learning paradigms. I had a big interest in semi-supervised learning, but that faded over time. I'm still quite interested in active learning, multiple-instance learning and other forms of weakly-supervised learning.
Fuxin Li, Cristian Sminchisescu. Convex Multiple Instance Learning by Estimating Likelihood Ratio, Advances in Neural Processing Systems (NIPS), 2010. Supplementary Material
Fuxin Li, Catalin Ionescu, Cristian Sminchisescu. Random Fourier approximations for skewed multiplicative histogram kernels. In German Association for Pattern Recognition (Deutsche Arbeitsgemeinschaft für Mustererkennung, DAGM), 2010. DAGM prize paper. Code availabe soon!
Fuxin Li, João Carreira, Cristian Sminchisescu. Object Recognition as Ranking Holistic Figure-Ground Hypotheses. In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2010 (First two authors contributed equally). Per-class accuracies for our VOC 2009 final results (37.24%)
Fuxin Li, Cristian Sminchisescu. The Feature Selection Path in Kernel Methods. In Artificial Intelligence and Statistics (AISTATS), 2010.
Fen Xia, Yanwu Yang, Liang Zhou, Fuxin Li, Min Cai, Daniel D. Zeng: A closed-form reduction of multi-class cost-sensitive learning to weighted multi-class learning. Pattern Recognition 42(7): 1572-1581 (2009).
Fuxin Li, Yunshan Fu, Yu-Hong Dai, Crisitian Sminchisescu, Jue Wang. Kernel Learning by Unconstrained Optimization. In Artificial Intelligence and Statistics (AISTATS), 2009.
Fen Xia, Wensheng Zhang, Fuxin Li, Yanwu Yang. Ranking with Decision Tree. Knowledge and Information Systems. 17(3):381-395 (2008)
Liang Zhou, Fuxin Li, Yanwu Yang. Path Algorithms for One-Class SVM. ISNN (1) 2008: 645-654
Fuxin Li, Jian Yang, Jue Wang. A Transductive Framework of Distance Metric Learning by Spectral Dimensionality Reduction. In Proceedings of International Conference on Machine Learning (ICML), 2007
Peng Jin, Danqing Zhu, Fuxin Li, Yunfang Wu. PKU: Combining Supervised Classifiers with Features Selection. In Proceedings of the 4th International Workshop on Semantic Evaluations (SemEval-2007), 2007.
Jian Yang, Fuxin Li, Jue Wang. A Better Scaled Local Tangent Space Alignment Algorithm. Proceedings of International Joint Conference on Neural Networks (IJCNN), 2005
Chen Shao, Wei Sun, Fuxin Li, Ruifeng Yang, Ling Zhang, Youhe Gao. Oscore: a combined score to reduce false negative rates for peptide identification in tandem mass spectrometry analysis. Journal of Mass Spectrometry. 2009(14):1, 25-31.
Linjie Wang, Fuxin Li, Wei Sun, Shuzhen Wu, Xiaorong Wang, Ling Zhang, Dexian Zheng, Jue Wang, and Youhe Gao. Concanavalin A-captured Glycoproteins in Healthy Human Urine. Molecular & Cellular Proteomics. 2006(5): 560 - 562
Wei Sun, Fuxin Li, Shuzhen Wu, Xiaorong Wang, Dexian Zheng, Jue Wang, Youhe Gao. Human urine proteome analysis by three separation approaches. Proteomics. 2005(5): 4994-5001
Fuxin Li, Wei Sun, Youhe Gao, Jue Wang. RScore: A Peptide Randomicity Score For Evaluating MS/MS Spectra. Rapid Communications in Mass Spectrometry. 2004(18):14,1655-1659
Wei Sun, Fuxin Li, Jue Wang, Dexian Zheng, Youhe Gao. AMASS: Software for Automatically Validating the Quality of MS/MS Spectrum From SEQUEST Results. Molecular & Cellular Proteomics. 2004(3): 1194-1199