数据挖掘张钧.doc

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Relevance units latent variable model and nonlinear dimensionality reduction. IEEE Transactions on Neural Networks, vol.21, issue.1,2010, pp. 123-135 . (sci000273339800010, Inspec 11037349, EI20100312637074).2 Jun Zhang, Junbin Gao, and Jinwen Tian. Relevance units machine based on Akaikes information criterion. In M. Ding, B. Bhanu, F.M. Wahl, J. Roberts (Eds): Proc. of SPIE, MIPPR 2009: Pattern Recognition and Computer Vision. vol.7496, pp. 749624-1 749624-7, 2009（EI20095112550534，Inspec11175656）3 Jun Zhang, Junbin Gao, David Tien and Shaoqun Zeng. RUM based calcium pulse modeling. 6th International Conference on Information Technology and Applications, ICITA 2009, Nov. 912, 2009, Hanoi, Vietnam. pp.164-168 (EI 20102613043378)4 Jun Zhang, Junbin Gao, David Tien and Jinwen Tian. A new organization method for massive raster data and vector data. 6th International Conference on Information Technology and Applications, ICITA 2009, Nov. 912, 2009, Hanoi, Vietnam. pp.161-163 (EI 20102613043377)5张钧,张宏,刘小茂,曾绍群. 双目立体视觉中物点定位的一种快速算法. 信息与控制. 2009,38(5):563-570.(Inspec11195739)6 Junbin Gao and Jun Zhang. Sparse kernel learning and the relevance units machine. In T. Theeramunkong et al.(Eds): PAKDD2009, LNAI 5476, pp.612-619, Springer-Verlag Berlin Heidelberg, 2009.( sci 000268632000057, Inspec10679372, EI20093012218223)7 张钧,王鹏. 一种新的矢量数据多边形的快速裁剪算法. 中国图象图形学报, 2008, 13(12): 2409-24138 Jun Zhang, Bing Yang, Xiaomao Liu, Xinxin Zhu, Shaoqun Zeng. Some properties of the fuzzy equivalence matrices. In S.J. Maybank, M. Ding, F. Wahl and Y. Zhu(Eds): Proc. of SPIE, MIPPR 2007: Pattern Recognition and Computer Vision. vol.6788, pp.67882B-1 67882B-7, 2007 (sci000252363600082, Inspec10001621, EI20081811236232)9 Bing Yang, Jun Zhang, Dajiang Shen, Jinwen Tian, Yongcai Liu. New image distance and its application in object recognition. In S.J. Maybank, M. Ding, F. Wahl and Y. Zhu(Eds): Proc. of SPIE, MIPPR 2007: Pattern Recognition and Computer Vision, vol.6788, pp.678815-1 678815-6,2007. (sci000252363600040，Inspec9996356, EI20081811236197)10 刘小茂,刘振丙,张钧.基于相似压缩的近似线性SVM. 信息与控制. 2007,36(5):610-615(Inspec10094090)11 刘小茂,全廷伟,张钧.线性支持向量分类机的平凡解. 华中科技大学学报(自然科学版).2007,35(10):57-59，66(EI20080311033211, Inspec10123359)2. 校内教学队伍情况2-1人员构成姓名性别出生年月职称学科专业备注张钧男1966.1副教授模式识别3、拟聘请校外专家情况（如果多名专家，可重复此表）3-1基本信息姓 名高俊斌性别男出生年月1962年8月国 籍澳大利亚E-mail jiushigao最终学历博士研究生职称教授办公电话[phone]最终学位理学博士职务学科带头人移动电话[phone]工作单位澳大利亚查尔斯特大学(Charles Sturt University, Australia)3-2教学科研情况近五年来讲授的主要研究生课程（含授课学校，课程名称、学时数、每年听课学生人数）；主持的代表性的研究课题（含课题名称、来源、年限、本人所起作用）；作为主要作者在国内外主要刊物发表的代表性相关论文（含题目、刊物名称与时间）；获得的代表性表彰/奖励（含奖项名称、授予单位、署名次序、时间）。近五年讲授的研究生课程时间授课学校课程名称学时数听课学生人数2006Charles Sturt University(CSU), AustraliaCurrent Programming24152007CSUMachine Learning24102008CSUData Mining24102009CSUComputational Intelligence24262010CSUCurrent Programming24163-2教学科研情况近五年主持的研究课题课题名称来源年限本人作用Dimensionality Reduction AlgorithmsCompetitive Grants from CSU2010.072011.07第一负责人Automatic detection of larger fragments in mining sites Newcrest Mining Pty Ltd, Australia2008.012010.12第一负责人非向量型Kernel学习机及其对动态形状模板的应用(60373090) 中国国家自然科学基金项目2004.012006.12第一负责人近五年发表的论文Edited Books1 Kok-Leong Ong, Wenyuan Li and Junbin Gao, The proceedings of the 2nd International Workshop on Integrating AI and DataMining (AIDM 2007), Gold Coast, Australia. December 2007, ISBN 978-1-920682-65-1, ISSN 1445-1336 (Vol. 84).2 Junbin Gao, Paul Kwan, Josiah Poon and Simon Poon, Advances and Issues in Biomedical Data Mining, Proceedings ofWorkshop on Advanced and Issues in Biomedical DataMining (AIBDM09) at PAKDD 2009, 27 April 2009, Bangkok, Thailand, Thammasat University Printing House, ISBN 978-974-446-382-5 Book Chapters3 Junbin Gao and Lei Zhang, The Error Bar Estimation for the Soft Classification with Gaussian Process Models, in Applied Soft Computing Technologies: The Challenge of Complexity, series of Advances in Soft Computing, Vol.XXXIII (2006), editors: Abraham, A.; Baets, B.; Koeppen, M. and Nickolay,B., pp669-677. ISSN: 1615-3871 4 Junbin Gao, Spline Functions and Their Application, Chapter 23, in Handbook of Modern Mathematics, Vol. V, editor-in-chief: L.C. Hsu, Huazhong University of Science and Technology Press House, ISBN 7-5609-2174-4, 1999. (in Chinese) 5 Junbin Gao, A remark on the interpolation by C1 quartic bivariate splines with boundary conditions, in A Friendly Collection of Mathematical Papers I, eds. by R.H.Wang and Y.S.Chou, Jilin University Press, Changchun, China 1990, pp99102.Published Journal Articles6 Junbin Gao, J. Zhang and D. Tien, Relevance Units Latent Variable Model and Nonlinear Dimensionality Reduction, IEEE Transactions on Neural Networks, Vol. 21:1 (2010), pp. 123-135 7 Junbin Gao, P. Kwan and D. Shi, Sparse Kernel Learning with LASSO and Its Bayesian Inference, Neural Networks, Vol. 23 (2010), Issue 2, pp 257-264 8 P. Kwan, Junbin Gao, Y. Guo and K. Kameyama, A Learning Framework for Adaptive Fingerprint Identification, International Journal of Pattern Recognition and Artificial Intelligence, Vol. 24:1 (2010), pp15 - 38. 9 Junbin Gao, P. Kwan and X. Huang, Comprehensive Analysis for the Local Fisher Discriminant Analysis, International Journal of Pattern Recognition and Artificial Intelligence, Vol. 23 (2009), 1129-1143. 3-2教学科研情况10 Junbin Gao, P. Kwan and Y. Guo, Robust Multivariate L1 Principal Component Analysis and Dimensionality Reduction, Neurocomputing, Vol. 72 (2009), pp 1242-1249. 11 Junbin Gao, Robust L1 Principal Component Analysis and Its Bayesian Variational Inference, Neural Computation, Vol.20:2 (2008), pp555-572 12 Y. Guo, Junbin Gao and P. Kwan, Twin Kernel Embedding, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 30 (2008), pp 1490-1495. 13 Y. Guo, Junbin Gao, P. Kwan and K.X. Hou, Visualization of Protein Structure Relationships Using Constrained Twin Kernel Embedding, Journal of Biomedical Science and Engineering, Vol. 1 (2008), pp 133-140.14 Junbin Gao, D.M. Shi and X.M. Liu, Significant Vector Learning to Construct Sparse Kernel Regression Modelling, Neural Networks, Vol 20 (2007), No. 7, pp 791-798. 15 X. Huang, W Lei, A.S.M. Sajeev and Junbin Gao, A new algorithm for removing node overlapping in graph visualization, Information Sciences, Vol.177 (2007), pp 2821-2844 16 Y. Guo, Junbin Gao, P. Kwan and K.X. Hou, Visualization of Protein Structure Relationships Using Constrained Twin Kernel Embedding, Journal of Biomedical Science and Engineering, Vol. 1 (2008), pp 133-140.17 Junbin Gao, D.M. Shi and X.M. Liu, Significant Vector Learning to Construct Sparse Kernel Regression Modelling, Neural Networks, Vol 20 (2007), No. 7, pp 791-798. 18 X. Huang, W Lei, A.S.M. Sajeev and Junbin Gao, A new algorithm for removing node overlapping in graph visualization, Information Sciences, Vol.177 (2007), pp 2821-2844 19 T. Tian, S. Xu, Junbin Gao and K. Burrage, Simulated maximum likelihood method for estimating kinetic rates in gene expression, Bioinformatics, Vol.23 (2007), pp 84-91. 20 X. Liu, B. Kong, Junbin Gao and J. Zhang, A sparse least squares support vector machine classifier, Pattern Recognition and Artificial Intelligence, Vol.20 (2007), p681-687. 21 D. Shi, Junbin Gao and G.S. Ng, The construction of wavelet network for speech signal processing, Neural Computing & Applications, Vol.15 (2006), pp217-222. 22 D. Shi, D.S. Yeung and Junbin Gao, Sensitivity analysis applied to the construction of radial basis function networks, Neural Networks, Vol. 18(2005), p951-957. Refereed Conference Papers23 X. Jiang, Junbin Gao, T. Wang and P. Kwan, Learning Gradient via Gaussian Process, M.J. Zaki et al. (Eds.): PAKDD 2010 (acceptance rate 10.1%), Part II, Lecture Notes on Artificial Intelligence, Vol. 6119, pp. 113-124, 2010. 24 Yi Guo, Junbin Gao and PaulW. Kwan, Regularized Kernel Local Linear Embedding on Dimensionality Reduction for Non-vectorial Data, A. Nicholson and X. Li (Eds.): AI 2009, Lecture Notes on Artificial Intelligence, Vol. 5866 (2009), pp. 240-249. Springer, Heidelberg 25 J. Zhang, Junbin Gao, and J. Tian, Relevance units machine based on akaikes information criterion, in Proceedings of the Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, ser. Pattern Recognition and Computer Vision, M. Ding, B. Bhanu, F. Wahl, and J. Roberts, Eds., vol. 7496. Yichang, China: SPIE, 2009, pp. 7496241-8.3-2教学科研情况26 A. OConnor, Junbin Gao and J. Louis, Termination Criteria for Evolutionary Algorithms, Proceeding of the 2009 International Conference on Genetic and Evolutionary Methods, CSREA Press 2009, pp 35-42.27 A. OConnor, Junbin Gao and J. Louis, Initiation of Evolutionary Algorithms, Proceeding of the 2009 International Conference on Genetic and Evolutionary Methods (GEM09), CSREA Press 2009, pp73-78.28 P. Kwan, Junbin Gao and Graham Leedham, A User-Centered Framework for Adaptive Fingerprint Identification, Lecture Notes on Computer Science, Vol.5477(2009), pp89-100, H. Chen et al. (Eds.): Pacific Asia Workshop on Intelligence and Security Informatics (PAISI 2009) joint with the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-09). 29 Junbin Gao and Jun Zhang, Sparse Kernel Learning and the Relevance Units Machine, Lecture Notes on Computer Science, Vol.5476(2009), pp612-619, T. Theeramunkong et al. (Eds.): Proceedings of The 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-09). 30 X. Huang, J. Yong, J. Li and Junbin Gao, Prediction of Student Actions Using Weighted Markov Models, Proceedings of 2008 IEEE International Symposium on IT in Medicine & Education (ITME 2008), pp 154-159, Xiamen, China31 Junbin Gao, M. Antolovich and P. Kwan, L1 LASSO and Its Bayesian Inference, Lecture Notes on Computer Science, Vol.5360 (2008), pp318324, Australian AI 08,W.Wobcke and M. Zhang (Eds.) ERA B Conference Citation Report: SCOPUS: 132 R. Xu, Junbin Gao and Michael Antolovich, Novel methods for high-resolution facial image capture using calibrated PTZ and static cameras, Proceedings of IEEE International Conference on Multimedia and Expo (ICME 2008), Hanover, Germany: pp45-48. ERA B Conference 33 A. OConnor, Junbin Gao and J. Louis, Using a Stochastic Funnel to find NLR Starting Values, Proceedings of The 2008 International Conference on Genetic and Evolutionary Methods (GEM08), pp96-102, USA, July 2008.34 M. Robards, Junbin Gao and P. Charlton, A Discriminant Analysis for Undersampled Data, Proceeding of 2nd International Workshop on Integrating AI and Data Mining (AIDM) at Australian AI 2007, CRPIT Vol 84, pp11-18. ERA B Conference 35 Junbin Gao and R. Xu, Mixture of the Robust L1 Distributions and Its Applications, Lecture Notes in Artificial Intelligence, Vol. 4830 (2007), pp26-35, a full paper in Australian AI 2007 (31% acceptance rate) ERA B Conference Citation Report: SCOPUS: 136 Y. Guo, Junbin Gao and P. Kwan, Twin kernel embedding with relaxed constraints on dimensionality reduction for structured data, Lecture Notes in Artificial Intelligence, Vol. 4830 (2007), pp659-663, a short paper in AI 2007 (63% acceptance rate) ERA B Conference Citation Report: SCOPUS: 237 Y. Guo, Junbin Gao and P. Kwan, Twin Kernel Embedding with Back Constraints, Workshop Proceeding of International Conference on Data Mining 2007, Oct 28-31 2007, Omaha NE, USA, pp. 319-324. DOI: 10.1109/ICDMW.2007.112 ERA A Conference38 Junbin Gao, Y. Guo and P. Kwan, Robust L1 PCA and Its Application in Image Denoising, Proceedings of SPIE, Volume 6786: MIPPR 2007 (Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition), Tianxu Zhang, Carl A. Nardell, Duane D. Smith, Hangqing Lu, Editors, 67860T, Nov. 15, 2007, doi:10.1117/12.774719 3-2教学科研情况39 P. Kwan, Junbin Gao and Y. Guo, A Learning Framework for Examiner-Centric Fingerprint Classification using Spectral Features, Proceedings of SPIE, Vol.6788, : MIPPR 2007 (Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition), Tianxu Zhang, Carl A. Nardell, Duane D. Smith, Hangqing Lu, Editors, 67881H, doi:10.1117/12.749777 40 Y. Guo and Junbin Gao, Integration of Shape Context and Semigroup Kernel in image classification, in Proceedings of the Sixth International Conference on Machine Learning and Cybernetics (ICMLC07), Hong Kong, 19-22 August 2007, pp181-186. ERA C Conference41 Y. Guo, Junbin Gao and P. Kwan, Learning Ou