Sciweavers

60
Voted
JMLR
2012

Algorithms for Learning Kernels Based on Centered Alignment

12 years 2 months ago
Algorithms for Learning Kernels Based on Centered Alignment
This paper presents new and effective algorithms for learning kernels. In particular, as shown by our empirical results, these algorithms consistently outperform the so-called uniform combination solution that has proven to be difficult to improve upon in the past, as well as other algorithms for learning kernels based on convex combinations of base kernels in both classification and regression. Our algorithms are based on the notion of centered alignment which is used as a similarity measure between kernels or kernel matrices. We present a number of novel algorithmic, theoretical, and empirical results for learning kernels based on our notion of centered alignment. In particular, we describe efficient algorithms for learning a maximum alignment kernel by showing that the problem can be reduced to a simple QP and discuss a one-stage algorithm for learning both a kernel and a hypothesis based on that kernel using an alignment-based regularization. Our theoretical results include a n...
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
Added 27 Sep 2012
Updated 27 Sep 2012
Type Journal
Year 2012
Where JMLR
Authors Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
Comments (0)