Computer Science ›› 2016, Vol. 43 ›› Issue (12): 139-145.doi: 10.11896/j.issn.1002-137X.2016.12.025
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SHEN Jian, JIANG Yun, ZHANG Ya-nan and HU Xue-wei
[1] Boser B E,Guyon I M,Vapnik V N.A training algorithm for optimal margin classifiers[M]∥Haussler D.eds.,5th Annual ACM Workshop on COLT,Pittsburgh,PA.ACM Press.,1992 [2] Vapnik V.The nature of statistical learning theory[M].New York:Springer-Verlag,1995 [3] Wang L P.Support vector machine:theory and application [M].Berlin:Springer-Verlag,2005 [4] Schoelkopf B,Smola A,Muller K R.Nonlinear component analysis as a kernel eigenvalue problem[J].Neural Computation,1998,10(5):1299-1319 [5] Scholkopf B,Mika S,Burges C J C,et al.Input space versus feature space in kernel-based methods[J].IEEE Transactions on Neural Network,1999,10(5):1000-1017 [6] Muller K R,Mika S,Ratsch G,et al.An introduction to kernel based learning algorithms[J].IEEE Transactions on Neural Networks,2001,12(2):181-201 [7] Mercer J.Functions of positive and negative type and their connection with the theory of integral equations[J].Philosophical Transactions of the Royal Society of London,Series A,1909,209:415-446 [8] Aronszajn N.Theory of reproducing kernels[J].Transactions of the American Mathematical Society,1950,68(3):337-404 [9] Aizerman A,Braverman E M,Rozoner L I.Theoretical foundations of the potential function method in pattern recognition learning[J].Automation and Remote Control,1964,25(5):821-837 [10] Smola A J,Scholkopf B.A tutorial on support vector regression[J].Statistics and Computing,2004,14(3):199-222 [11] Burges C J C.A tutorial on support vector machines for pattern recognition[J].Data Mining and Knowledge Discovery,1998,2(2):121-167 [12] Kerm P V.Adaptive kernel density estimation[J].Stata Jour-nal,2003,3(2):148-156 [13] Scholkopf B,Mika S,Smola A,et al.Kernel PCA pattern reconstruction via approximation preimages[C]∥Proceedings of the International Conference of Artificial Neural Networks.Skovde,Sweden:IEEE,1998:147-152 [14] Mika S,Ratsch G,Weston J,et al.Fisher discriminant analysis with kernels[C]∥Proceedingsof the Conference on Neural Networks for Signal Processing.Washington D.C.,USA:IEEE,1999:41-48 [15] Baudat G,Anouar F.Generalized discriminant analysis using a kernel approach[J].Neural Computation,2000,12(10):2385-2404 [16] Wang Hong-qiao,Sun Fu-chun,Cai Yan-ning,et al.On multiple kernel learning methods[J].Acta Automatic Sinica,2010,36(8):1037-1050(in Chinese) 汪洪桥,孙富春,蔡艳宁,等.多核学习方法[J].自动化学报,2010,6(8):1037-1050 [17] Huang C,Chen Y,Chen W,et al.Gastroesophageal Reflux Disea-se Diagnosis Using Hierarchical Heterogeneous Descriptor Fusion Support Vector Machine[C]∥IEEE Engineering in Medicine and Biology Society.2015:1-10 [18] Penga S,Hua Qing-hua,Chen Yin-li,et al.Interactive,Improved support vector machine algorithm for heterogeneous data [J].Pattern Recognition,2015,48(6):2072-2083 [19] Sonnenburg S,Ratsch G,Schafer C,et al.Large scale multiple kernel learning[J].The Journal of Machine Learning Research,2006,7(7):1531-1565 [20] Xiao Yu-lin,Zhong Shang-ping.An improved online multiplekernel classification algorithm based on double updating online learning [C]∥2014 International Conference on Cloud Computing and Internet of Things.2014:109-113 [21] Bach F R.Consistency of the group Lasso and multiple kernel learning[J].The Journal of Machine Learning Research,2008,9(6):1179-1225 [22] Cortes C,Mohri M,Rostamizadeh A.Learning sequence kernels[C]∥Proceedings of the International Conference on Machine Learning for Signal Processing.Washington D.C.,USA:IEEE,2008:2-8 [23] Rakotomamonjy A,Bach F R,Canu S,et al.Simple MKL[J].The Journal of Machine Learning Research,2008,9(11):2491-2521 [24] Zheng D N,Wang J X,Zhao Y N.Nonflat function estimation with a multi-scale support vector regession[J].Neurocompu-ting,2006,70(1-3):420-429 [25] Wang Jing-yan,Bensmailc H,Gao Xin.Feature selection andmulti-kernel learning for sparse representation on a manifold [J].Neural Networks,2014,51(3):9-16 [26] Xua Lin,Feng Yan-qiu,Liu Xiao-yun,et al.Robust GRAPPAreconstruction using sparse multi-kernel learning with least squares support vector regression [J].Magnetic Resonance Imaging,2014,2(1):91-101 [27] Wang Jing-yan,Huang Jian-hua,Sun Yi-jun,et al.Feature selection and multi-kernel learning for adaptive graph regularized nonnegative matrix factorization[J].Expert Systems with Applications,2015,2(3):1278-1286 [28] Lanckriet G R G,Cristianini N,Bartlett P,et al.Learning the kernel matrix with semi definite programming[J].The Journal of Machine Learning Research,2004,5(1):27-72 [29] Lee W J,Verzakov S,Duin R P.Kernel combination versus classifier combination[C]∥Proceedings of the 7th International Workshop on Multiple Classifier Systems.Prague,Czech Republic:Springer,2007:22-31 [30] Bi J B,Zhang T,Bennett K P.Column-generation boostingmethods for mixture of kernels[C]∥Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Disco-very and Data Mining.Seattle,USA:ACM,2004:521-526 [31] Kingsbury N,Tay D B H,Palaniswami M.Multi-Scale Kernel Me-thods for Classification[C]∥Proc.of the IEEE Workshop on Machine Learning for Signal Processing.Mystic,USA,2005:43-48 [32] Yang Zhen,Guo Jun,Xu Wei-ran.Multi-Scale Support Vector Machine for Regression Estimation[C]∥ Proc.of the 3rd International Symposiumon Neural Networks.Chengdu,China,2006:1030-1037 [33] Izmailov R,Bassu D,McIntosh A,et al.Application of multi-scale singular vector decomposition to vessel classification in overhead satellite imagery[C]∥Seventh International Confe-rence on Digital Image Processing (ICDIP 2015).2015 [34] Vapnik V N.统计学习理论[M].许建华,张学工,译.北京:电子工业出版社,2009 [35] Ding Shi-fei,Qi Bing-juan,Tan Hong-yan.An overview on theory and algorithm of support vector machines [J].Journal of University of Electronic Science and Technology of China,2011,0(1):2-10(in Chinese) 丁世飞,齐丙娟,谭红艳.支持向量机理论与算法研究综述[J].电子科技大学学报,2011,0(1):2-10 [36] Platt J C,Cristianini N,Shawe-Taylor J.Large Margin DAGs for multiclass classification[J].Advances in Neural Information Processing Systems,2000,12(3):547-553 [37] Manivannan K,Aggarwal P,Devabhaktuni V,et al.Particulate matter characterization by gray level co-occurrence matrix based support vector machines[J].Journal of hazardous materials,2012,223-224(2):94-103 [38] Hsu C W,Lin C J.A Comparison of Methods for MulticlassSupport Vector Machines [J].IEEE Transactions on Neural Networks,2002,3(3):415-425 [39] Kre U,et al.Pairwise classification and support vector machines[C]∥Advances in Kernel Methods.MIT Press,1999:255-268 [40] Larochelle H,Bengio Y.Classification using Discriminative Restricted Boltzmann Machines[C]∥Proceedings of the 25th International Conference on Machine Learning,2008.Helsinki,Finland,2008:1-8 |
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