1323 search results - page 157 / 265 » Feature Extraction for Machine Learning: Logic-Probabilistic... |
119
click to vote
CVPR
2003
IEEE
16 years 2 months ago
2003
IEEE
We consider the problem of learning with instances defined over a space of sets of vectors. We derive a new positive definite kernel f(A B) defined over pairs of matrices A B base...
97
Voted
ICML
2009
IEEE
16 years 1 months ago
2009
IEEE
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...
106
click to vote
ECML
2006
Springer
15 years 4 months ago
2006
Springer
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
98
Voted
ICML
2009
IEEE
16 years 1 months ago
2009
IEEE
Despite popular belief, boosting algorithms and related coordinate descent methods are prone to overfitting. We derive modifications to AdaBoost and related gradient-based coordin...
101
click to vote
CVPR
2009
IEEE
16 years 7 months ago
2009
IEEE
Most modern computer vision systems for high-level
tasks, such as image classification, object recognition and
segmentation, are based on learning algorithms that are
able to se...