265 search results - page 34 / 53 » Learning with Kernels and Logical Representations |
AAAI
2007
14 years 1 months ago
2007
The importance of the efforts towards integrating the symbolic and connectionist paradigms of artificial intelligence has been widely recognised. Integration may lead to more e...
KI
2007
Springer
14 years 5 months ago
2007
Springer
Abstract. Markov logic, as a highly expressive representation formalism that essentially combines the semantics of probabilistic graphical models with the full power of first-orde...
TNN
2011
13 years 5 months ago
2011
Domain adaptation solves a learning problem in a target domain by utilizing the training data in a different but related source domain. Intuitively, discovering a good feature rep...
ML
2008
ACM
13 years 11 months ago
2008
ACM
Abstract We present a new margin-based approach to first-order rule learning. The approach addresses many of the prominent challenges in first-order rule learning, such as the comp...
FGR
2011
IEEE
13 years 2 months ago
2011
IEEE
— Many modern computer vision algorithms are built atop of a set of low-level feature operators (such as SIFT [1], [2]; HOG [3], [4]; or LBP [5], [6]) that transform raw pixel va...