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Dimensionality Reduction and Principal Surfaces via Kernel Map Manifolds

机译：通过核图流形减少维数和主曲面

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Samuel Gerber; Tolga Tasdizen; Ross Whitaker;
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年度 2009
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1. Dimension reduction in radio maps based on the supervised kernel principal component analysis [J] . Bing Jia, Baoqi Huang, Hepeng Gao, Soft computing: A fusion of foundations, methodologies and applications . 2018,第23期

机译：基于监督内核主成分分析的无线电贴图尺寸减小
2. Dimension reduction in radio maps based on the supervised kernel principal component analysis [J] . Bing Jia, Baoqi Huang, Hepeng Gao, Soft computing: A fusion of foundations, methodologies and applications . 2018,第23期

机译：基于监督内核主成分分析的无线电贴图尺寸减小
3. Dimensionality reduction of collective motion by principal manifolds [J] . Gajamannage Kelum, Butail Sachit, Porfiri Maurizio, Physica, D. Nonlinear phenomena . 2015,第Null期

机译：主流形减少集体运动的维数
4. Dimensionality reduction and principal surfaces via Kernel Map Manifolds [C] . Gerber Samuel, Tasdizen Tolga, Whitaker Ross IEEE International Conference on Computer Vision;ICCV 2009 . 2009

机译：通过内核映射歧管进行降维和主曲面
5. Nonlinear dimensionality reduction using probabilistic principal surfaces. [D] . Chang, Kui-yu. 2000

机译：使用概率主曲面进行非线性降维。
6. Kernel Principal Component Analysis for dimensionality reduction in fMRI-based diagnosis of ADHD [O] . Gagan S. Sidhu, Nasimeh Asgarian, Russell Greiner, 2012

机译：基于fMRI的ADHD诊断中的降维核主成分分析
7. Kernel Principal Component Analysis for dimensionality reduction in fMRI-based diagnosis of ADHD [O] . Gagan S Sidhu, Nasimeh eAsgarian, Russell eGreiner, 2012

机译：基于fmRI的aDHD诊断中维数降低的核主成分分析

Dimensionality Reduction and Principal Surfaces via Kernel Map Manifolds

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