| [1] CUCKER F, SMALE S. On the Mathematical Foundations of Lear-ning. Bulletin of the American Mathematical Society, 2001, 39(1): 1-49.
[2] ZHENG D N, WANG J X, ZHAO Y N. Nonflat Function Estimation with a Multi-scale Support Vector Regression. Neurocomputing, 2006, 70(1/2/3): 420-429.
[3] SAUNDERS C, GAMMERMAN A, VOVK V. Ridge Regression Learning Algorithm in Dual Variables // Proc of the 15th International Conference on Machine Learning. New York, USA: ACM, 1998: 515-521.
[4] YANG H Q, XU Z L, YE J P, et al. Efficient Sparse Generalized Multiple Kernel Learning. IEEE Transactions on Neural Networks, 2011, 22(3): 433-446.
[5] 邵喜高.基于统计学习理论的多核预测模型研究及应用.博士学位论文.长沙:中南大学, 2013.
(SHAO X G. The Research and Application of Multiple Kernel Prediction Model Based on Statistical Learning Theory. Ph.D. Dissertation. Changsha, China: Central South University, 2013.)
[6] KINGSBURY N, TAY D, PALANISWAMI M. Multi-scale Kernel Methods for Classification // Proc of the IEEE Workshop on Machine Learning for Signal Processing. Washington, USA: IEEE Press, 2005: 43-48.
[7] 汪洪桥,蔡艳宁,孙富春,等.多尺度核方法的自适应序列学习及应用.模式识别与人工智能, 2011, 24(1): 72-81.
(WANG H Q, CAI Y N, SUN F C. Adaptive Sequence Learning and Applications for Multi-scale Kernel Method. Pattern Recognition and Artificial Intelligence, 2011, 24(1): 72-81.)[8] XU Y L, CHEN D R, LI H X, et al. Least Square Regularized Regression in Sum Space. IEEE Transactions on Neural Networks and Learning Systems, 2013, 24(4): 635-646.
[9] SHAMIR O, SREBRO N. Distributed Stochastic Optimization and Learning[C/OL]. [2018-11-12]. https://arxiv.org/pdf/1408.5294.pdf.
[10] ZHANG Y C, DUCHI J, WAINWRIGHT M. Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates. Journal of Machine Learning Research, 2015, 16: 3299-3340.
[11] M CKE N, BLANCHARD G. Parallelizing Spectral Algorithms for Kernel Learning. Journal of Machine Learning Research, 2016, 19: 1-29.
[12] LIN S B, GUO X, ZHOU D X. Distributed Learning with Regula-rized Least Squares. Journal of Machine Learning Research, 2017, 18: 1-31.
[13] GUO Z C, LIN S B, ZHOU D X. Learning Theory of Distributed Spectral Algorithm. Inverse Problems, 2017, 33(7). DOI:10.1088/1361-6420/aa72b2.
[14] GUO Z C, SHI L, WU Q. Learning Theory of Distributed Regre-ssion with Bias Corrected Regularization Kernel Network. Journal of Machine Learning Research, 2017, 18: 1-25.
[15] JOSHI B, IUTZELER F, AMINI M R. Large-Scale Asynchronous Distributed Learning Based on Parameter Exchanges[J/OL]. [2018-11-12]. https://arxiv.org/pdf/1705.07751.pdf.
[16] TIKHONOV A N. Regularization of Incorrectly Posed Problems. Soviet Mathematics Doklady, 1963, 4(1): 1624-1627.
[17] ARONSZAJN N. Theory of Reproducing Kernels. Transactions of the American Mathematical Society, 1950, 68(3): 337-404.
[18] CUCKER F, ZHOU D X. Learning Theory: An Approximation Theory Viewpoint. Cambridge, UK: Cambridge University Press, 2007. |
2019, Vol. 32 
