Minimax convergence rates for kernel CCA
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Pages (from-to) | 183-190 |
Journal / Publication | Journal of Multivariate Analysis |
Volume | 150 |
Publication status | Published - 1 Sept 2016 |
Externally published | Yes |
Link(s)
Abstract
Consistency of kernel canonical correlation analysis (kernel CCA) has been established while its optimal convergence rate remains unknown. In this paper we derive rigorous upper and lower bounds for the convergence rate of the weight functions in kernel CCA. In particular the optimal convergence rate is shown to only depend on the rate of decay of the eigenvalues of the covariance operators.
Research Area(s)
- Canonical correlation analysis, Covariance operator, Cross-covariance operator, Lower bound
Citation Format(s)
Minimax convergence rates for kernel CCA. / Fan, Zengyan; Lian, Heng.
In: Journal of Multivariate Analysis, Vol. 150, 01.09.2016, p. 183-190.
In: Journal of Multivariate Analysis, Vol. 150, 01.09.2016, p. 183-190.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review