资源分类
》 资源 》论文》On the Size of the Online Kernel Sparsification Dictionary

On the Size of the Online Kernel Sparsification Dictionary

2020-02-28 | |  59 |   48 |   0

Abstract

We analyze the size of the dictionary constructed from online kernel sparsification, using a novel formula that expresses the expected determinant of the kernel Gram matrix in terms of the eigenvalues of the covariance operator. Using this formula, we are able to connect the cardinality of the dictionary with the eigen-decay of the covariance operator. In particular, we show that under certain technical conditions, the size of the dictionary will always grow sublinearly in the number of data points, and, as a consequence, the kernel linear regressor constructed from the resulting dictionary is consistent.

上一篇：Inferring Latent Structure From Mixed Real and Categorical Relational Data

下一篇：Deep Lambertian Networks

用户评价
全部评价

热门资源

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • The Variational S...

    Unlike traditional images which do not offer in...

  • Learning to learn...

    The move from hand-designed features to learned...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...

  • Learning to Predi...

    Much of model-based reinforcement learning invo...