83 search results - page 4 / 17 » Rademacher Chaos Complexities for Learning the Kernel Proble... |
JMLR
2012
11 years 10 months ago
2012
In recent years there has been a lot of interest in designing principled classification algorithms over multiple cues, based on the intuitive notion that using more features shou...
BMVC
2010
13 years 5 months ago
2010
Kernel methods yield state-of-the-art performance in certain applications such as image classification and object detection. However, large scale problems require machine learning...
NIPS
2004
13 years 9 months ago
2004
The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
CORR
2011
Springer
12 years 11 months ago
2011
Springer
Learning theory has largely focused on two main learning scenarios. The first is the classical statistical setting where instances are drawn i.i.d. from a fixed distribution and...
PR
2008
13 years 7 months ago
2008
It is generally believed that quadratic discriminant analysis (QDA) can better fit the data in practical pattern recognition applications compared to linear discriminant analysis ...