Statistical analysis of the moving least-squares method with unbounded sampling
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Luoqing Li | Hong Chen | Fangchao He | Luoqing Li | Hong Chen | Fangchao He
[1] Don R. Hush,et al. Optimal Rates for Regularized Least Squares Regression , 2009, COLT.
[2] D. H. McLain,et al. Drawing Contours from Arbitrary Data Points , 1974, Comput. J..
[3] Ding-Xuan Zhou,et al. Concentration estimates for learning with unbounded sampling , 2013, Adv. Comput. Math..
[4] Lorenzo Rosasco,et al. Elastic-net regularization in learning theory , 2008, J. Complex..
[5] Luoqing Li,et al. Learning rates of multi-kernel regularized regression , 2010 .
[6] Lean Yu,et al. An evolutionary programming based asymmetric weighted least squares support vector machine ensemble learning methodology for software repository mining , 2012, Inf. Sci..
[7] Xinge You,et al. Generalization performance of magnitude-preserving semi-supervised ranking with graph-based regularization , 2013, Inf. Sci..
[8] Yiming Ying,et al. Support Vector Machine Soft Margin Classifiers: Error Analysis , 2004, J. Mach. Learn. Res..
[9] Hong-Yan Wang,et al. Concentration estimates for the moving least-square method in learning theory , 2011, J. Approx. Theory.
[10] Jianqing Fan,et al. Local polynomial modelling and its applications , 1994 .
[11] Jean-Yves Audibert,et al. Robust linear least squares regression , 2010, 1010.0074.
[12] Felipe Cucker,et al. Learning Theory: An Approximation Theory Viewpoint (Cambridge Monographs on Applied & Computational Mathematics) , 2007 .
[13] Cheng Wang,et al. Optimal learning rates for least squares regularized regression with unbounded sampling , 2011, J. Complex..
[14] H. Wendland. Local polynomial reproduction and moving least squares approximation , 2001 .
[15] D. Levin,et al. Hermite type moving-least-squares approximations , 2006, Comput. Math. Appl..
[16] Ding-Xuan Zhou,et al. High order Parzen windows and randomized sampling , 2009, Adv. Comput. Math..
[17] Jun Fan,et al. Learning theory approach to minimum error entropy criterion , 2012, J. Mach. Learn. Res..
[18] Ding-Xuan Zhou,et al. The covering number in learning theory , 2002, J. Complex..
[19] G. Fasshauer. Toward approximate moving least squares approximation with irregularly spaced centers , 2004 .
[20] Ding-Xuan Zhou,et al. Learning Theory: An Approximation Theory Viewpoint , 2007 .
[21] Milan Hladík,et al. On the possibilistic approach to linear regression models involving uncertain, indeterminate or interval data , 2013, Inf. Sci..
[22] Dao-Hong Xiang,et al. Moving least-square method in learning theory , 2010, J. Approx. Theory.
[23] Yiming Ying,et al. Learning Rates of Least-Square Regularized Regression , 2006, Found. Comput. Math..
[24] A. Caponnetto,et al. Optimal Rates for the Regularized Least-Squares Algorithm , 2007, Found. Comput. Math..
[25] Yaron Lipman. Stable Moving Least-Squares , 2009, J. Approx. Theory.
[26] Yiming Ying,et al. Multi-kernel regularized classifiers , 2007, J. Complex..
[27] Ding-Xuan Zhou,et al. Capacity of reproducing kernel spaces in learning theory , 2003, IEEE Transactions on Information Theory.
[28] Vladimir Vapnik,et al. Statistical learning theory , 1998 .