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[1] W. Hoeffding. The strong law of large numbers for u-statistics. , 1961 .
[2] Ing Rj Ser. Approximation Theorems of Mathematical Statistics , 1980 .
[3] T. Cover,et al. Determinant inequalities via information theory , 1988 .
[4] L. Elsner,et al. The Hoffman-Wielandt inequality in infinite dimensions , 1994 .
[5] T. Philips,et al. The Moment Bound is Tighter than Chernoff's Bound for Positive Tail Probabilities , 1995 .
[6] S. Boucheron,et al. A sharp concentration inequality with applications , 1999, Random Struct. Algorithms.
[7] V. Koltchinskii,et al. Random matrix approximation of spectra of integral operators , 2000 .
[8] Christopher K. I. Williams,et al. Using the Nyström Method to Speed Up Kernel Machines , 2000, NIPS.
[9] S. Boucheron,et al. A sharp concentration inequality with applications , 1999, Random Struct. Algorithms.
[10] Carl D. Meyer,et al. Matrix Analysis and Applied Linear Algebra , 2000 .
[11] OF Epartment,et al. A NEW LOOK AT NEWTON’S INEQUALITIES , 2000 .
[12] Adam Krzyzak,et al. A Distribution-Free Theory of Nonparametric Regression , 2002, Springer series in statistics.
[13] Michael I. Jordan,et al. Kernel independent component analysis , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..
[14] Anthony Widjaja,et al. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond , 2003, IEEE Transactions on Neural Networks.
[15] Shie Mannor,et al. The kernel recursive least-squares algorithm , 2004, IEEE Transactions on Signal Processing.
[16] Gilles Blanchard,et al. Statistical properties of Kernel Prinicipal Component Analysis , 2019 .
[17] Petros Drineas,et al. On the Nyström Method for Approximating a Gram Matrix for Improved Kernel-Based Learning , 2005, J. Mach. Learn. Res..
[18] Mikio L. Braun,et al. Spectral properties of the kernel matrix and their relation to kernel methods in machine learning , 2005 .
[19] Yaakov Engel,et al. Algorithms and representations for reinforcement learning (עם תקציר בעברית, תכן ושער נוסף: אלגוריתמים וייצוגים ללמידה מחיזוקים.; אלגוריתמים וייצוגים ללמידה מחיזוקים.) , 2005 .
[20] Don R. Hush,et al. An Explicit Description of the Reproducing Kernel Hilbert Spaces of Gaussian RBF Kernels , 2006, IEEE Transactions on Information Theory.
[21] Xin Xu,et al. A Sparse Kernel-Based Least-Squares Temporal Difference Algorithm for Reinforcement Learning , 2006, ICNC.
[22] Zaïd Harchaoui,et al. Testing for Homogeneity with Kernel Fisher Discriminant Analysis , 2007, NIPS.
[23] Sergios Theodoridis,et al. Online Kernel-Based Classification Using Adaptive Projection Algorithms , 2008, IEEE Transactions on Signal Processing.
[24] Zaïd Harchaoui,et al. A Fast, Consistent Kernel Two-Sample Test , 2009, NIPS.
[25] Jan Peters,et al. Incremental Sparsification for Real-time Online Model Learning , 2010, AISTATS.
[26] Rong Jin,et al. Improved Bound for the Nystrom's Method and its Application to Kernel Classification , 2011, ArXiv.
[27] Rong Jin,et al. Improved Bounds for the Nyström Method With Application to Kernel Classification , 2011, IEEE Transactions on Information Theory.