683 search results - page 53 / 137 » Generalization Bounds for Learning Kernels |
154
Voted
ICCV
2005
IEEE
16 years 5 months ago
2005
IEEE
In recent years Kernel Principal Component Analysis (Kernel PCA) has gained much attention because of its ability to capture nonlinear image features, which are particularly impor...
149
Voted
CIE
2007
Springer
15 years 10 months ago
2007
Springer
In the framework of parameterized complexity, exploring how one parameter affects the complexity of a different parameterized (or unparameterized problem) is of general interest....
128
Voted
TIP
2008
15 years 3 months ago
2008
Previous research applying kernel methods such as support vector machines (SVMs) to hyperspectral image classification has achieved performance competitive with the best available ...
116
Voted
PKDD
2009
Springer
15 years 10 months ago
2009
Springer
Abstract. We present a method for applying machine learning algorithms to the automatic classification of astronomy star surveys using time series of star brightness. Currently su...
141
Voted
COLT
2005
Springer
15 years 9 months ago
2005
Springer
We study the rank, trace-norm and max-norm as complexity measures of matrices, focusing on the problem of fitting a matrix with matrices having low complexity. We present generali...