63 search results - page 1 / 13 » Learning low-rank kernel matrices |
AAAI
2012
11 years 7 months ago
2012
Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
We propose a general and efficient algorithm for learning low-rank matrices. The proposed algorithm converges super-linearly and can keep the matrix to be learned in a compact fac...
CORR
2008
Springer
13 years 5 months ago
2008
Springer
How many random entries of an n
ICML
2004
IEEE
14 years 6 months ago
2004
IEEE
The problem of computing low rank approximations of matrices is considered. The novel aspect of our approach is that the low rank approximations are on a collection of matrices. W...
CORR
2012
Springer
12 years 1 months ago
2012
Springer
We present a novel approach to learn a kernelbased regression function. It is based on the use of conical combinations of data-based parameterized kernels and on a new stochastic ...