In:
Abstract and Applied Analysis, Hindawi Limited, Vol. 2014 ( 2014), p. 1-8
Abstract:
We study an empirical eigenfunction-based algorithm for ranking with a data dependent hypothesis space. The space is spanned by certain empirical eigenfunctions which we select by using a truncated parameter. We establish the representer theorem and convergence analysis of the algorithm. In particular, we show that under a mild condition, the algorithm produces a satisfactory convergence rate as well as sparse representations with respect to the empirical eigenfunctions.
Type of Medium:
Online Resource
ISSN:
1085-3375
,
1687-0409
Language:
English
Publisher:
Hindawi Limited
Publication Date:
2014
detail.hit.zdb_id:
2064801-7
SSG:
17,1
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