21 search results - page 1 / 5 » Learning the Kernel Matrix with Semi-Definite Programming |
ICML
2002
IEEE
14 years 5 months ago
2002
IEEE
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Many kernel learning methods have to assume parametric forms for the target kernel functions, which significantly limits the capability of kernels in fitting diverse patterns. Som...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
Previous studies of Non-Parametric Kernel (NPK) learning usually reduce to solving some Semi-Definite Programming (SDP) problem by a standard SDP solver. However, time complexity ...
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
Kernel nonnegative matrix factorization (KNMF) is a recent kernel extension of NMF, where matrix factorization is carried out in a reproducing kernel Hilbert space (RKHS) with a f...
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) ...