Kernels and Regularization on Graphs

机译：图的核与正则化

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We introduce a family of kernels on graphs based on the notion of regularization operators. This generalizes in a natural way the notion of regularization and Greens functions, as commonly used for real valued functions, to graphs. It turns out that diffusion kernels can be found as a special case of our reasoning. We show that the class of positive, monotonically decreasing functions on the unit interval leads to kernels and corresponding regularization operators.

机译：我们基于正则化运算符的概念在图上引入了一系列内核。这自然地将正则化和Greens函数（通常用于实值函数）的概念推广到图形。事实证明，可以将扩散核作为我们推理的特殊情况。我们表明，单位间隔上的正，单调递减函数的类导致核和相应的正则化运算符。

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《16th Annual Conference on Learning Theory and 7th Kernel Workshop, COLT/Kernel 2003 Aug 24-27, 2003 Washington, DC, USA》|2003年|p.144-158|共15页
会议地点 Washington DC(US);Washington DC(US);Washington DC(US);Washington DC(US);Washington DC(US);Washington DC(US)
作者
Alexander J. Smola; Risi Kondor;
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作者单位

Machine Learning Group, RSISE Australian National University Canberra, ACT 0200, Australia;

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原文格式 PDF
正文语种 eng
中图分类自动化技术、计算机技术;
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3. Spatial-Spectral Graph Regularized Kernel Sparse Representation for Hyperspectral Image Classification [J] . Jianjun Liu, Zhiyong Xiao, Yufeng Chen, ISPRS International Journal of Geo-Information . 2017,第8期

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4. Kernels and Regularization on Graphs [C] . Alexander J. Smola, Risi Kondor, Lecture Notes in Artificial Intelligence 2777 Annual Conference on Learning Theory . 2003

机译：内核和正规化图
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7. Kernels and Regularization on Graphs [O] . Alexander J. Smola, Risi Kondor 2003

机译：图的核与正则化

Kernels and Regularization on Graphs

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