暂无分享,去创建一个
[1] S. Saitoh. Integral Transforms, Reproducing Kernels and Their Applications , 1997 .
[2] Vladimir Vovk,et al. On-Line Regression Competitive with Reproducing Kernel Hilbert Spaces , 2005, TAMC.
[3] Philip M. Long,et al. WORST-CASE QUADRATIC LOSS BOUNDS FOR ON-LINE PREDICTION OF LINEAR FUNCTIONS BY GRADIENT DESCENT , 1993 .
[4] Grace Wahba,et al. Spline Models for Observational Data , 1990 .
[5] W. Rudin. Real and complex analysis , 1968 .
[6] Steven A. Orszag,et al. CBMS-NSF REGIONAL CONFERENCE SERIES IN APPLIED MATHEMATICS , 1978 .
[7] A. Timan. Theory of Approximation of Functions of a Real Variable , 1994 .
[8] W. N. MUNDY,et al. Treatise I , 2004, Avicenna, ›The Healing, Logic: Isagoge‹.
[9] Alexander J. Smola,et al. Learning with kernels , 1998 .
[10] Andrew Donald Booth,et al. Theory of the transmission and processing of information , 1961 .
[11] Felipe Cucker,et al. On the mathematical foundations of learning , 2001 .
[12] O. Hanner. On the uniform convexity ofLp andlp , 1956 .
[13] A. Kolmogoroff,et al. Zur Grossenordnung Des Restgliedes Fourierscher Reihen Differenzierbarer Funktionen , 1935 .
[14] Alexander Gammerman,et al. On-line Prediction with Kernels and the Complexity Approximation Principle , 2004, UAI.
[15] Harold Widom,et al. Rational approximation and n-dimensional diameter☆ , 1972 .
[16] Joram Lindenstrauss. Classical Banach Spaces II: Function Spaces , 1979 .
[17] B. Carl,et al. Entropy, Compactness and the Approximation of Operators , 1990 .
[18] Manfred K. Warmuth,et al. Exponentiated Gradient Versus Gradient Descent for Linear Predictors , 1997, Inf. Comput..
[19] V. Bargmann. On a Hilbert space of analytic functions and an associated integral transform part I , 1961 .
[20] L. Pontrjagin,et al. Sur Une Propriete Metrique de la Dimension , 1932 .
[21] Yuri Kalnishkan,et al. The weak aggregating algorithm and weak mixability , 2005, J. Comput. Syst. Sci..
[22] Dean Phillips Foster. Prediction in the Worst Case , 1991 .
[23] David E. Edmunds,et al. CIarkson's InequaIities, Besoy Spaces and Triebel–Sobolev Spaces , 1988 .
[24] Don R. Hush,et al. An Explicit Description of the Reproducing Kernel Hilbert Spaces of Gaussian RBF Kernels , 2006, IEEE Transactions on Information Theory.
[25] Gábor Lugosi,et al. Prediction, learning, and games , 2006 .
[26] H. Hanche-Olsen. ON THE UNIFORM CONVEXITY OF L , 2005 .
[27] L. Rubel,et al. Constructive Function Theory , 1984 .
[28] H. Triebel,et al. Function Spaces, Entropy Numbers, Differential Operators: Function Spaces , 1996 .
[29] Alexander J. Smola,et al. Support Vector Machine Reference Manual , 1998 .
[30] Vladimir Vovk,et al. Leading strategies in competitive on-line prediction , 2006, Theor. Comput. Sci..
[31] J. Cooper,et al. Theory of Approximation , 1960, Mathematical Gazette.
[32] Vladimir Vovk,et al. Competing with wild prediction rules , 2005, Machine Learning.
[33] H. Hanche-Olsen. On the uniform convexity of L^p , 2005, math/0502021.
[34] J. A. Clarkson. Uniformly convex spaces , 1936 .
[35] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[36] Vladimir Vovk,et al. Competing with Markov prediction strategies , 2006, ArXiv.
[37] Radakovič. The theory of approximation , 1932 .
[38] Vladimir Vovk. Non-asymptotic calibration and resolution , 2007, Theor. Comput. Sci..
[39] 齋藤 三郎. Integral transforms, reproducing kernels and their applications , 1997 .
[40] Claudio Gentile,et al. Adaptive and Self-Confident On-Line Learning Algorithms , 2000, J. Comput. Syst. Sci..
[41] Vladimir Vovk,et al. Competing with Stationary Prediction Strategies , 2006, COLT.
[42] L. Ahlfors. Complex Analysis , 1979 .
[43] N. Aronszajn. Theory of Reproducing Kernels. , 1950 .
[44] Manfred K. Warmuth,et al. Averaging Expert Predictions , 1999, EuroCOLT.
[45] Vladimir Vovk,et al. Predictions as Statements and Decisions , 2006, COLT.
[46] G. F. Clements. Entropies of sets of functions of bounded variation , 1963 .
[47] V. Vovk. Competitive On‐line Statistics , 2001 .
[48] N. Bary,et al. Treatise of Trigonometric Series , 1966 .
[49] Ingo Steinwart,et al. On the Influence of the Kernel on the Consistency of Support Vector Machines , 2002, J. Mach. Learn. Res..