Waegeman, W., Baets, B.D., Boullart, L.: Kernel-based learning methods for pref- erence aggregation. 4OR 7(2) (2009) 169-189Waegeman, W., De Baets, B., Boullart, L.: Kernel-based learning methods for preference aggregation. 4OR: A Quarterly Journal of Operations Research 7, ...
Kernel-based learning methods The kernel function—a function returning the inner product between mapped data points in a higher dimensional space—is a foundational building block for kernel-based learning methods. Such learning takes place in the feature space so long as the learning algorithm can ...
Ot her Kernel-Based Learning Met hods A Review Tong Zhang An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods, Nello Cristianini and John Shawe-Taylor, Cambridge University Press, Cambridge, U.K., 2000, 189 pp., ISBN 0-521-78019-5. n eed t o in clude...
Kernel-basedLearningMethods byNelloCristianiniandJohn Shawe-Taylor ISBN:0521780195 CambridgeUniversityPress?2000(190pages) ThisisthefirstcomprehensiveintroductiontoSVMs,a newgenerationlearningsystembasedonrecent advancesinstatisticallearningtheory;itwillhelp
we presented a connection between boosting and kernel-based methods. we showed that in the context of regularized least-squares, boosting with a weak learner is equivalent to using a boosting kernel. this connection also implies that learning rates and consistency analysis on kernel based methods (...
改进之,注意到一些算法只用到向量内积,因此可以跳过映射ΦΦ一步到位,因此引入核方法kernel methods Def. Kernels 函数K:X×X→RK:X×X→R称为XX上的核kernel 引入核的思想,是为了在内积上等价于某个映射Φ:X→HΦ:X→H;且KK的计算量要小于映射+高维空间内积(例如O(N),O(dim(H))O(N),O(dim(H...
Hofmann, T., Schölkopf, B., & Smola, A. J. (2008). Kernel methods in machine learning. ...
Adaptive Kernel Based Machine Learning Methods.Adaptive Kernel Based Machine Learning Methods.Learning machinesAlgorithmsComputerized tomographyLearningNumerical analysisKernelResearch results obtained from this project address the kernel selection problem in machine learning. Specifically, motivated from the need of...
Kernel Methods (KMs) are powerful machine learning techniques that can alleviate the data representation problem as they substitute scalar product between feature vectors with similarity functions (kernels) directly defined between data instances, e.g., syntactic trees, (thus features are not needed any...
摘要: Kernel machines; Kernel methods Kernel-based learning refers to a family of data-driven estimation and machine learning techniques that rely on positive definite kernel functions (short: kernels)...DOI: 10.1007/978-1-4419-9863-7_604 收藏...