Design of a multiple kernel learning algorithm for LS-SVM by convex programming
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Chuanhou Gao | Zhonghang Xia | Ling Jian | Xijun Liang | Chuanhou Gao | Xijun Liang | Zhonghang Xia | Ling-xiang Jian
[1] Catherine Blake,et al. UCI Repository of machine learning databases , 1998 .
[2] Bernhard Schölkopf,et al. Learning with kernels , 2001 .
[3] Gunnar Rätsch,et al. Large Scale Multiple Kernel Learning , 2006, J. Mach. Learn. Res..
[4] Chuanhou Gao,et al. Application of Least Squares Support Vector Machines to Predict the Silicon Content in Blast Furnace Hot Metal , 2008 .
[5] Nello Cristianini,et al. A statistical framework for genomic data fusion , 2004, Bioinform..
[6] Johan A. K. Suykens,et al. Benchmarking Least Squares Support Vector Machine Classifiers , 2004, Machine Learning.
[7] Murat Dundar,et al. A fast iterative algorithm for fisher discriminant using heterogeneous kernels , 2004, ICML.
[8] Jieping Ye,et al. Multi-class Discriminant Kernel Learning via Convex Programming , 2008, J. Mach. Learn. Res..
[9] Alexander J. Smola,et al. Learning the Kernel with Hyperkernels , 2005, J. Mach. Learn. Res..
[10] C. Berg,et al. Harmonic Analysis on Semigroups: Theory of Positive Definite and Related Functions , 1984 .
[11] Stephen P. Boyd,et al. Semidefinite Programming , 1996, SIAM Rev..
[12] Knud D. Andersen,et al. The Mosek Interior Point Optimizer for Linear Programming: An Implementation of the Homogeneous Algorithm , 2000 .
[13] Ivor W. Tsang,et al. Efficient hyperkernel learning using second-order cone programming , 2006, IEEE Trans. Neural Networks.
[14] Hua Xiang,et al. Perturbation analysis of generalized saddle point systems , 2006 .
[15] Johan A. K. Suykens,et al. L2-norm multiple kernel learning and its application to biomedical data fusion , 2010, BMC Bioinformatics.
[16] Michael I. Jordan,et al. Multiple kernel learning, conic duality, and the SMO algorithm , 2004, ICML.
[17] Dmitrij Frishman,et al. MIPS: a database for genomes and protein sequences , 1999, Nucleic Acids Res..
[18] Johan A. K. Suykens,et al. Low rank updated LS-SVM classifiers for fast variable selection , 2008, Neural Networks.
[19] Jos F. Sturm,et al. A Matlab toolbox for optimization over symmetric cones , 1999 .
[20] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.
[21] Gavin C. Cawley,et al. Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters , 2007, J. Mach. Learn. Res..
[22] S. Sathiya Keerthi,et al. Evaluation of simple performance measures for tuning SVM hyperparameters , 2003, Neurocomputing.
[23] Johan A. K. Suykens,et al. Optimal control by least squares support vector machines , 2001, Neural Networks.
[24] Andrew McCallum,et al. Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data , 2004, J. Mach. Learn. Res..
[25] Mohamed Cheriet,et al. Model selection for the LS-SVM. Application to handwriting recognition , 2009, Pattern Recognit..
[26] Gene H. Golub,et al. Matrix computations , 1983 .
[27] Nello Cristianini,et al. Learning the Kernel Matrix with Semidefinite Programming , 2002, J. Mach. Learn. Res..
[28] Domenico Conforti,et al. Kernel based support vector machine via semidefinite programming: Application to medical diagnosis , 2010, Comput. Oper. Res..
[29] Stephen P. Boyd,et al. Optimal kernel selection in Kernel Fisher discriminant analysis , 2006, ICML.
[30] Johan A. K. Suykens,et al. Least Squares Support Vector Machine Classifiers , 1999, Neural Processing Letters.
[31] Xuan Li,et al. Association of tissue lineage and gene expression: conservatively and differentially expressed genes define common and special functions of tissues , 2010, BMC Bioinformatics.