The Rademacher Complexity of Linear Transformation Classes

The Rademacher Complexity of Linear Transformation Classes
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线性变换类的 Rademacher 复杂度

DOI:
10.1007/11776420_8
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发表时间:
2006
期刊:
2016 IEEE 16th International Conference on Data Mining (ICDM)
影响因子:
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通讯作者:
Andreas Maurer
Andreas Maurer
中科院分区:
--
文献类型:
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作者:
Andreas Maurer

文献摘要

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给出了从Hilbert空间H到有限维空间的线性变换类的经验Rademacher复杂性和期望Rademacher复杂性的界。这些结果为图的正则化和多任务子空间学习提供了泛化保证。
Bounds are given for the empirical and expected Rademacher complexity of classes of linear transformations from a Hilbert space H to a finite dimensional space. The results imply generalization guarantees for graph regularization and multi-task subspace learning.