148 search results - page 15 / 30 » Feature space perspectives for learning the kernel |
SSPR
2010
Springer
13 years 6 months ago
2010
Springer
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
TCS
2008
13 years 7 months ago
2008
This paper studies a novel paradigm for learning formal languages from positive and negative examples which consists of mapping strings to an appropriate highdimensional feature s...
CVPR
2011
IEEE
13 years 3 months ago
2011
IEEE
Kernel methods have been popular over the last decade to solve many computer vision, statistics and machine learning problems. An important, both theoretically and practically, op...
AAAI
2011
12 years 8 months ago
2011
Transfer learning allows knowledge to be extracted from auxiliary domains and be used to enhance learning in a target domain. For transfer learning to be successful, it is critica...
JCP
2008
13 years 8 months ago
2008
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...