141 search results - page 1 / 29 » Learning r-of-k Functions by Boosting |
ALT
2004
Springer
14 years 1 months ago
2004
Springer
We investigate further improvement of boosting in the case that the target concept belongs to the class of r-of-k threshold Boolean functions, which answer “+1” if at least r o...
COLT
2000
Springer
13 years 9 months ago
2000
Springer
Boosting algorithms like AdaBoost and Arc-GV are iterative strategies to minimize a constrained objective function, equivalent to Barrier algorithms. Based on this new understandi...
CVPR
2006
IEEE
14 years 6 months ago
2006
IEEE
Motion estimation for applications where appearance undergoes complex changes is challenging due to lack of an appropriate similarity function. In this paper, we propose to learn ...
ICML
2008
IEEE
14 years 5 months ago
2008
IEEE
We introduce a boosting framework to solve a classification problem with added manifold and ambient regularization costs. It allows for a natural extension of boosting into both s...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
In this paper, we present a new interpretation of AdaBoost.ECC and AdaBoost.OC. We show that AdaBoost.ECC performs stage-wise functional gradient descent on a cost function, defin...