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Study on ice phase change prediction model for transmission lines based on multiphysics coupling. [PDF]

Sci Rep
Pei Y, Wang Q, Wang L, Zuo S, Zhang H, Jing L.   +5 more
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Kernel Methods

2015
What the reader should know to understand this chapter • Notions of calculus. • Chapters 5, 6, and 7. • Although the reading of Appendix D is not mandatory, it represents an advantage for the chapter understanding.
CAMASTRA, Francesco, Vinciarelli, Alessandro   +1 more
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A Novel Kernel Method for Clustering

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005
Kernel Methods are algorithms that, by replacing the inner product with an appropriate positive definite function, implicitly perform a nonlinear mapping of the input data into a high-dimensional feature space. In this paper, we present a kernel method for clustering inspired by the classical K-Means algorithm in which each cluster is iteratively ...
CAMASTRA F, VERRI, ALESSANDRO
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Eigenvalues Ratio for Kernel Selection of Kernel Methods

Proceedings of the AAAI Conference on Artificial Intelligence, 2015
The selection of kernel function which determines the mapping between the input space and the feature space is of crucial importance to kernel methods. Existing kernel selection approaches commonly use some measures of generalization error, which are usually difficult to estimate and have slow convergence rates.
Yong Liu 0018, Shizhong Liao
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The Reproducing Kernel Method. II

Journal of Mathematical Physics, 1972
The explicit solution of the Cauchy problem ∂N/∂t = HN by means of reproducing kernels is obtained under various forms: conformal mapping expansions, Sheffer polynomial expansion, polynomials orthogonal on a family of curves; the convergence is studied for both Szegö and Bergman kernels.
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Kernel Methods for Clustering

2006
Kernel Methods are algorithms that implicitly perform, by replacing the inner product with an appropriate Mercer Kernel, a nonlinear mapping of the input data to a high dimensional Feature Space. In this paper, we describe a Kernel Method for clustering.
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Kernel methods for melanoma recognition.

Studies in health technology and informatics, 2006
Skin cancer is a spreading disease in the western world. Early detection and treatment are crucial for improving the patient survival rate. In this paper we present two algorithms for computer assisted diagnosis of melanomas. The first is the support vector machines algorithm, a state-of-the-art large margin classifier, which has shown remarkable ...
La Torre, Elisabetta, TOMMASI, TATIANA, CAPUTO, BARBARA, GIGANTE, Giovanni Ettore   +3 more
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